Advances in Child Development and Behavior Volume 35

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ADVANCES IN CHILD DEVELOPMENT AND BEHAVIOR

VOLUME 35

Page i

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Contributors to This Volume David F. Bjorklund

Nancy Geyelin Margie

Patrick T. Davies

Daniel Messinger

Bruce J. Ellis

Nora S. Newcombe

Alan Fogel

Robert C. Pianta

Graham J. Hitch

Kristin R. Ratliff

Neil Horton

Justin S. Rosenberg

Kyle Kearnan

Monique Sénéchal

Melanie Killen

Stefanie Sinno

Laurence B. Leonard

Melissa L. Sturge-Apple

Marianne E. Lloyd

John N. Towse

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ADVANCES IN CHILD DEVELOPMENT AND BEHAVIOR

edited by

Robert V. Kail Department of Psychological Sciences Purdue University West Lafayette, IN 47907, USA

Volume 35

AMSTERDAM • BOSTON • HEIDELBERG • LONDON • NEW YORK • OXFORD • PARIS • SAN DIEGO • SAN FRANCISCO • SINGAPORE • SYDNEY • TOKYO Academic Press is an imprint of Elsevier

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Academic Press is an imprint of Elsevier 84 Theobald’s Road, London WC1X 8RR, UK Radarweg 29, PO Box 211, 1000 AE Amsterdam, The Netherlands Linacre House, Jordan Hill, Oxford OX2 8DP, UK 30 Corporate Drive, Suite 400, Burlington, MA 01803, USA 525 B Street, Suite 1900, San Diego, CA 92101-4495, USA First edition 2007 Copyright © 2007 Elsevier Inc. All rights reserved No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form or by any means electronic, mechanical, photocopying, recording or otherwise without the prior written permission of the publisher Permissions may be sought directly from Elsevier’s Science & Technology Rights Department in Oxford, UK: phone (+44) (0) 1865 843830; fax (+44) (0) 1865 853333; email: [email protected]. Alternatively you can submit your request online by visiting the Elsevier web site at http://elsevier.com/locate/permissions, and selecting Obtaining permission to use Elsevier material Notice No responsibility is assumed by the publisher for any injury and/or damage to persons or property as a matter of products liability, negligence or otherwise, or from any use or operation of any methods, products, instructions or ideas contained in the material herein. Because of rapid advances in the medical sciences, in particular, independent verification of diagnoses and drug dosages should be made ISBN: 978-0-12-009735-7 ISSN: 0065-2407 (Series)

For information on all Academic Press publications visit our website at books.elsevier.com

Printed and bound in USA 07 08 09 10 11

10 9 8 7 6 5 4 3 2 1

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Contents Contributors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

ix

Preface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

xi

Evolved Probabilistic Cognitive Mechanisms: An Evolutionary Approach to Gene ⫻ Environment ⫻ Development Interactions DAVID F. BJORKLUND, BRUCE J. ELLIS, AND JUSTIN S. ROSENBERG I. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . II. Central Tenets of Evolutionary Psychology and Developmental Systems Theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . III. What is the Perceived Incompatibility of Evolved Cognitive Mechanisms and Probabilistic Epigenesis? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . IV. Evolved Probabilistic Cognitive Mechanisms . . . . . . . . . . . . . . . . . . . . . . . . . V. What’s in a Name? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1 3 15 22 28 29 29

Development of Episodic and Autobiographical Memory: A Cognitive Neuroscience Perspective NORA S. NEWCOMBE, MARIANNE E. LLOYD AND KRISTIN R. RATLIFF I. Differentiating Infantile and Childhood Amnesia . . . . . . . . . . . . . . . . . . . . . . . II. Architecture of the Human Memory System . . . . . . . . . . . . . . . . . . . . . . . . . . III. Brain Bases of Human Memory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . IV. Memory in the First 2 Years . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . V. Implicit Memory in the Absence of Explicit Memory? . . . . . . . . . . . . . . . . . . VI. Are There Biological Bases for the Lifting of Infantile Amnesia? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VII. Are There Biological Bases for the Lifting of Childhood Amnesia? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VIII. Alternative Conceptualizations of the Development of Episodic Memory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . IX. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

40 43 47 52 55 58 62 69 72 73

Advances in the Formulation of Emotional Security Theory: An Ethologically Based Perspective PATRICK T. DAVIES AND MELISSA L. STURGE-APPLE I. Overview of the Principles, Processes, and Pathways in Emotional Security Theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . II. Distinctions between Security in the Interparental and Parent–Child Subsystems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

90 94

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Contents III. IV. V.

Family Origins and Correlates of Emotional Security . . . . . . . . . . . . . . . . . . . Emotional Insecurity and Children’s Developmental Trajectories . . . . . . . . . . Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Acknowledgment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

107 122 129 130 130

Processing Limitations and the Grammatical Profile of Children with Specific Language Impairment LAURENCE B. LEONARD I. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . II. Profiles of SLI across Languages . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . III. Alternative Accounts of SLI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . IV. Processing Limitations in SLI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . V. Implications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VI. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

139 141 146 147 165 166 167 167

Children's Experiences and Judgments about Group Exclusion and Inclusion MELANIE KILLEN, STEFANIE SINNO, AND NANCY GEYELIN MARGIE I. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . II. Social Exclusion Based on Gender . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . III. Social Exclusion Based on Race/Ethnicity . . . . . . . . . . . . . . . . . . . . . . . . . . . IV. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

173 181 194 204 209 210

Working Memory as the Interface between Processing and Retention: A Developmental Perspective JOHN N. TOWSE, GRAHAM J. HITCH, AND NEIL HORTON I. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . II. The Concept of Working Memory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . III. The Development of Working Memory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . IV. Explaining Complex Span in Children . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . V. Taking Developmental Questions about Working Memory Seriously . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VI. Theories of Working Memory in Children: an Integration . . . . . . . . . . . . . . . . VII. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Acknowledgment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

219 221 225 227 239 241 245 246 246

Developmental Science and Education: The NICHD Study of Early Child Care and Youth Development Findings from Elementary School ROBERT C. PIANTA I. Background and Design of the NICHD SECCYD Studies on Schooling . . . . . II. The NICHD SECCYD Classroom Observations and Outcome Assessments . .

254 256

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Contents III.

IV. V. VI. VII. VIII.

The Nature and Quality of the Instructional and Social Environment in Classroom Settings in Grades 1, 3, and 5: Descriptions of Classroom Processes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Are Classroom Experiences Related to Features of Teachers and Classrooms? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Are Child Outcomes Associated with Teacher or Classroom Characteristics That Are the Focus of Education Policy? . . . . . . . . . . . . . . . . . Do Experiences in Classrooms Matter for Development? . . . . . . . . . . . . . . . . Limitations of the NICHD SECCYD Studies on Schooling . . . . . . . . . . . . . . . Conclusions and Implications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

vii

263 267 270 275 284 285 289 290

The Role of Morphology in Reading and Spelling MONIQUE SÉNÉCHAL AND KYLE KEARNAN I. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . II. The Morphological Structure of Languages . . . . . . . . . . . . . . . . . . . . . . . . . . . III. Morphological Knowledge . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . IV. Morphological Knowledge and Reading . . . . . . . . . . . . . . . . . . . . . . . . . . . . . V. Morphological Knowledge and Spelling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VI. Morphological Awareness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VII. Summary and Concluding Remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

297 298 300 304 309 313 320 321

The Interactive Development of Social Smiling DANIEL MESSINGER AND ALAN FOGEL I. Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . II. Early Smiling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . III. Quantity and Quality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . IV. The Interactive Development of Smiling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . V. Smiling and Attention to the Caregiver . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VI. Smiling and Referential Communication . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VII. Pragmatics: The Representativeness, Discriminant, and Predictive Validity of Infant Smiling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VIII. Summary and Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

354 357 358 358

Author Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

367

Subject Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

387

Contents of Previous Volumes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

405

328 333 337 347 351 353

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Contributors

DAVID F. BJORKLUND Department of Psychology, Florida Atlantic University, Boca Raton, Florida 33431, USA PATRICK T. DAVIES Department of Clinical and Social Sciences in Psychology, University of Rochester, Rochester, New York 14627, USA BRUCE J. ELLIS John and Doris Norton School of Family and Consumer Sciences, University of Arizona, Tucson, Arizona 85721, USA ALAN FOGEL Department of Psychology, University of Utah, Salt Lake City, Utah 84112, USA GRAHAM J. HITCH Department of Psychology, University of York, York, Y010 5DD, United Kingdom NEIL HORTON Department of Psychology, Lancaster University, Bailrigg, Lancaster, LA1 4YF, United Kingdom KYLE KEARNAN Department of Psychology, Carleton University, Ottawa, Ontario K1S 0W4, Canada MELANIE KILLEN Department of Human Development, University of Maryland, College Park, Maryland 20742, USA LAURENCE B. LEONARD Department of Speech, Language, and Hearing Sciences, Purdue University, West Lafayette, Indiana 47907, USA MARIANNE E. LLOYD Department of Psychology, Seton Hall University, South Orange, New Jersey 07079, USA NANCY GEYELIN MARGIE Department of Human Development, University of Maryland, College Park, Maryland 20742, USA DANIEL MESSINGER Department of Psychology, University of Miami, Coral Gables, Florida 33124, USA

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Contributors

NORA S. NEWCOMBE Department of Psychology, Temple University, Philadelphia, Pennsylvania 19122, USA ROBERT C. PIANTA Center for Advanced Study of Teaching and Learning, University of Virginia, Charlottesville, Virginia 22908, USA KRISTIN R. RATLIFF Department of Psychology, Temple University, Philadelphia, Pennsylvania 19122, USA JUSTIN S. ROSENBERG Department of Psychology, Florida Atlantic University, Boca Raton, Florida 33431, USA MONIQUE SÉNÉCHAL Department of Psychology, Carleton University, Ottawa, Ontario K1S 5B6, Canada STEFANIE SINNO Department of Human Development, University of Maryland, College Park, Maryland 20742, USA MELISSA L. STURGE-APPLE Mt. Hope Family Center, University of Rochester, Rochester, New York 14627, USA JOHN N. TOWSE Department of Psychology, Lancaster University, Bailrigg, Lancaster, LA1 4YF, United Kingdom

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Preface Advances in Child Development and Behavior is designed to provide scholarly technical articles and to provide a place for publication of scholarly speculation. In these critical reviews, recent advances in the field are summarized and integrated, complexities are exposed, and fresh viewpoints are offered. These reviews should be useful not only to the expert in the area but also to the general reader. No attempt is made to organize each volume around a particular theme or topic. Manuscripts are solicited from investigators conducting programmatic work on problems of current and significant interest. The editor often encourages the preparation of critical syntheses dealing intensively with topics of relatively narrow scope but of considerable potential interest to the scientific community. Contributors are encouraged to criticize, integrate, and stimulate, but always within a framework of high scholarship. Although appearance in the volumes is ordinarily by invitation, unsolicited manuscripts will be accepted for review. All papers—whether invited or submitted— receive careful editorial scrutiny. Invited papers are automatically accepted for publication in principle, but usually require revision before final acceptance. Submitted papers receive the same treatment except that they are not automatically accepted for publication even in principle, and may be rejected. I acknowledge with gratitude the aid of my home institution, Purdue University, which generously provided time and facilities for the preparation of this volume. Robert V. Kail

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EVOLVED PROBABILISTIC COGNITIVE MECHANISMS: AN EVOLUTIONARY APPROACH TO GENE ⫻ ENVIRONMENT ⫻ DEVELOPMENT INTERACTIONS

David F. Bjorklund a, Bruce J. Ellis b, and Justin S. Rosenberg a a

DEPARTMENT OF PSYCHOLOGY, FLORIDA ATLANTIC UNIVERSITY, BOCA RATON, FL 33431, USA b JOHN AND DORIS NORTON SCHOOL OF FAMILY AND CONSUMER SCIENCES, UNIVERSITY OF ARIZONA, TUCSON, AZ 85721, USA

I. II.

INTRODUCTION CENTRAL TENETS OF EVOLUTIONARY PSYCHOLOGY AND DEVELOPMENTAL SYSTEMS THEORY A. EVOLUTIONARY PSYCHOLOGY B. DEVELOPMENTAL SYSTEMS THEORY C. SUMMARY OF THE MAJOR ASSUMPTIONS OF EVOLUTIONARY PSYCHOLOGY AND DEVELOPMENTAL SYSTEMS THEORY

III.

WHAT IS THE PERCEIVED INCOMPATIBILITY OF EVOLVED COGNITIVE MECHANISMS AND PROBABILISTIC EPIGENESIS? A. CLAIMS OF GENETIC DETERMINISM AND UNREALISTIC PLASTICITY B. EXPLAINING PHENOTYPIC PLASTICITY

IV.

EVOLVED PROBABILISTIC COGNITIVE MECHANISMS A. GENE ⫻ ENVIRONMENT ⫻ DEVELOPMENT INTERACTIONS B. LANGUAGE DEVELOPMENT AND EVOLVED PROBABILISTIC COGNITIVE MECHANISMS C. PREPARED LEARNING

V.

WHAT’S IN A NAME?

ACKNOWLEDGMENTS REFERENCES

I. Introduction Evolutionary psychology has increasingly captured the attention and imagination of academics and lay people alike. One part of this trend has been the rising popularity of evolutionary psychology in developmental science (e.g., Burgess & MacDonald, 2005; Ellis & Bjorklund, 2005). Along with new devotees to the field, however, there have also been critics (see, e.g., Buller, 2005; Caporael, 2003), with developmental scientists counted among them. Indeed, developmental psychologists

1 Advances in Child Development and Behavior R.V. Kail : Editor

Copyright © 2007 Elsevier Inc. All rights reserved.

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have often been more reticent than their peers in other subdisciplines of psychology to embrace evolutionary psychology. There are a number of reasons for this reluctance. Charlesworth (1992), for example, noted that developmental psychologists have long been concerned with the health and welfare of children, what he referred to as meliorism, and many perceive modern evolutionary theory as the antithesis of this perspective, viewing it as harsh and replete with social Darwinism. Somewhat relatedly, developmental psychologists have traditionally been interested in factors contributing to individual differences in children, whereas evolutionary psychology is more focused on species-typical universals (e.g., Tooby & Cosmides, 1990, 1992). Methodologically, developmental psychologists have viewed evolutionary psychology’s concern with distal, as opposed to proximal, factors as presenting insurmountable problems (one cannot travel backward through time to test phylogenetic factors). Many of these problems are more apparent than real (e.g., contemporary evolutionary psychology does not advocate a form of social Darwinism, can contribute to an understanding of individual differences and a promotion of child welfare, and does assess proximal causes of contemporary behavior). This has been recognized by many developmental psychologists (e.g., see Bjorklund & Pellegrini, 2000, 2002; Bugental, 2000; Burgess & MacDonald, 2005; Ellis & Bjorklund, 2005; Geary, 1995, 1998), and developmental psychology’s reluctance to embrace evolutionary psychology is waning. However, a subset of developmental psychologists—developmental systems theorists—who, on the face of it, would be seem to be likely advocates of an evolutionary psychology approach because of their emphasis on biological development, are actually among its harshest critics. The reason behind this antipathy lies in the perceived incompatibility of the core tenets of the two approaches: evolved cognitive mechanisms for proponents of evolutionary psychology and probabilistic epigenesis for proponents of developmental systems theory. In this chapter, we contrast and seek to integrate the concepts of evolved cognitive mechanisms and probabilistic epigenesis in explaining regularities in children’s development. In doing so, we seek to present a new approach to gene ⫻ environment ⫻ development interactions. The focus of this approach is on cognitive adaptations that are presumed to have a genetically monomorphic structure.1 Complex cognitive adaptations require the coordinated expression of large numbers of genes during development (Tooby & Cosmides, 1992; Bittner & Friedman, 2000). Many of these genes possess different alleles at given loci. When these allelic variations are neutral with regard to fitness outcomes (i.e., when these variations are not relevant to the development and functioning of the adaptation), 1

Of course it is also critical to explain the evolution and development of adaptations that have a genetically polymorphic structure. Such explanations are highly complex and beyond the scope of the current chapter; instead, we refer readers to our detailed treatment of these issues in a separate manuscript (Ellis et al., 2006).

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the resulting adaptation is considered to have a genetically monomorphic structure. Meaningful phenotypic variation in such adaptations arises from the interaction between the monomorphic genetic structure and the individual’s environment.2 Examples of such presumably monomorphic, species-typical cognitive adaptations considered in this chapter include theory of mind, auditory species-identification learning, language acquisition, and prepared learning. In the following sections we first describe and contrast the central tenets of evolutionary psychology and developmental systems theory, focusing on the concepts of evolved cognitive mechanisms from evolutionary psychology and probabilistic epigenesis from developmental systems theory. We then identify perceived incompatibilities between these two approaches and argue that differences between these positions are resolvable. We next propose the integrative concept of evolved probabilistic cognitive mechanisms, defined as cognitive mechanisms that have evolved to solve recurrent problems faced by ancestral populations, are highly probable when species-typical environments are encountered, and are products of emerging developmental systems that have evolved over the course of the ontogenies of a species’ ancestors. By providing a new way of looking at the nature of gene ⫻ environment ⫻ development interaction and its relation to evolutionary change, we believe that this concept affords a partial resolution of the conflicts between evolutionary psychology and developmental systems theory.

II. Central Tenets of Evolutionary Psychology and Developmental Systems Theory A. EVOLUTIONARY PSYCHOLOGY Evolutionary psychology is the application of the principles and knowledge of evolutionary biology to psychological theory and research. Its central assumption is that the human brain comprises a large number of specialized mechanisms that were shaped by natural selection over vast periods of time to solve recurrent problems associated with survival and reproduction faced by our ancestors (Symons, 1995; Tooby & Cosmides, 1992, 2005). These problems include such things as choosing which foods to eat, negotiating social hierarchies, dividing investment among offspring, and selecting mates. 2

By contrast, many alleles have different fitness values in different environments or life stages (Bittner & Friedman, 2000). In this case, polyallelic variation contributes to systematic individual differences in the development and functioning of complex traits. These individual differences arise from a complex interplay between the polymorphic genes and the environment (see Ellis et al., 2006). For example, Caspi et al. (2002) have shown that the influence of childhood maltreatment on the development of antisocial behavior in men is moderated by a functional polymorphism in the gene encoding the neurotransmitter-metabolizing enzyme monamine oxidase (see also Caspi et al., 2003).

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1. Evolved Cognitive Mechanisms What evolved, according to evolutionary psychologists, are cognitive mechanisms shaped by natural selection to (a) detect and encode information associated with recurrent problems of survival and reproduction in ancestral environments and (b) generate physiological activity and manifest behavior directed at solving the specific problem that brought the mechanism online. According to Tooby and Cosmides (1992), evolved cognitive mechanisms “in interaction with environmental input, generate manifest behavior. The causal link between evolution and behavior is made through psychological mechanisms” (p. 277). From this perspective, natural selection has operated at the cognitive level, such that information-processing mechanism evolved to solve real-world problems. The field of evolutionary psychology focuses on identifying these problems, developing models of the brain–mind mechanisms that may have evolved to solve them, and testing these models in research (Buss, 1995; Tooby & Cosmides, 1992, 2005). Most research in evolutionary psychology focuses on information-processing mechanisms because it is at this level where invariances occur. These mechanisms mediate the effects of genes and environments on cognition and behavior. That is, through their effects on molecular and cellular processes during development, structured gene ⫻ environment interactions reliably generate species-typical cognitive mechanisms (neural circuits), which in turn regulate development and expression of behavioral phenotypes.3 Evolved cognitive mechanisms are underpinned by universal genetic programs and shared by all biologically normal members of the species. 2. Emphasis on Universal Features of the Human Mind Evolutionary psychologists’ primary focus is on species-universal characteristics of the mind. Indeed, evolutionary psychologists assert that a core set of universal cognitive mechanisms comprises our shared human nature (Tooby & Cosmides, 1992). Central to this argument is the distinction between evolved, underlying cognitive mechanisms and manifest behavior. Tooby and Cosmides (1990, 1992) stress that, despite individual differences in actual behavior, all human beings possess the same set of evolved psychological mechanisms. Individual differences in behavior are due primarily to environmental differences in interaction with these universally inherited cognitive mechanisms, not the evolved psychological mechanisms themselves. For instance, the specific language one speaks is a matter of environmental input. However, children universally apply species-typical (and species-specific) cognitive mechanisms in 3

At a technical level, regulation refers to the role of specific neural circuits in coordinating the expression and use of trait-specific gene products and environmental elements in shaping behavioral phenotypes (see extensive discussion in West-Eberhard, 2003).

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making sense of the verbal input that surrounds them, resulting in some children speaking Chinese and others speaking French, for instance. The principal concern of evolutionary psychologists is to discover how the mind works, which requires an understanding of this species-typical cognitive architecture. Tooby and Cosmides (1990) argue that natural selection acts to reduce individual differences. Although some variability within a breeding population is necessary to combat parasites (Ridley, 1993) and to provide a range of possible reactions to changing environments, such variation must be superficial so as not to interfere with species-universal adaptations. Although some evolutionary psychologists recognize the potential importance of individual differences and interpret them from an adaptationist perspective (e.g., Belsky, Steinberg, & Draper, 1991; Buss & Greiling, 1999; Ellis, Jackson, & Boyce, in press; Ellis, Simpson, & Campbell, 2002; Figueredo et al., 2006), the primary focus of mainstream evolutionary psychologists remains on species universals and not individual differences. 3. Historical Nature of Biological Adaptations A central assumption of evolutionary psychology is that mechanisms evolved to solve specific adaptive problems encountered in ancestral environments; thus, the concept of biological adaptation is necessarily a historical one. Genes associated with more-successful phenotypes are transmitted with greater frequency from one generation to the next than genes associated with less-successful phenotypes, resulting, eventually, in species-level changes. When we claim that the thick insulating coat of the polar bear is an adaptation, we are claiming that possession of that trait advanced reproductive success in ancestral environments. All claims about adaptation are claims about the past because natural selection is a gradual, cumulative process. The polar bear’s thick coat arose through natural selection because it served to ward off the bitter-cold arctic weather during the animal’s evolutionary history. However, traits that served adaptive functions and thus were selected for in past environments may not be adaptive in present or future environments. In a globally warmed near future, for example, the polar bear’s lustrous pelt may become a handicap that reduces the fitness of its owner due to stress from overheating. In sum, when environments change, the conditions that proved advantageous to the evolution of a given trait may no longer exist; yet, the trait often remains in place for some time because evolutionary change occurs slowly. Such vestigial traits are eventually weeded out by natural selection (if they consistently detract from fitness) (Durrant & Ellis, 2003). In the field of evolutionary psychology it is commonly thought that changes wrought by civilization over the past 10,000 years have radically changed our adaptive landscape as a species. That is, the contemporary environmental landscape scarcely resembles the environment of even our recent ancestors. Humans last shared a common ancestor with our closest living relatives, chimpanzees (Pan troglodytes) and bonobos (Pan paniscus), 6–8 million years ago. Based on

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fossil, archeological, and genetic evidence (see Mithen, 1996; Olson, 2002; Stringer & Andrews, 2005; Tattersal, 1998), the genus Homo first appeared about 2.5 million years ago in Africa (Homo habilis), where it evolved into anatomically modern humans as early as 160,000 years ago (McDougall, Brown, & Fleagle, 2005). This time period of human evolution roughly corresponds to the Pleistocene era: the 2-million-year period prior to the emergence of agriculture, some 10,000 years ago. Based on fossil and archeological evidence and the lifestyles of modern hunter–gatherers, evolutionary psychologists believe that our Pleistocene ancestors lived in small nomadic groups (between 30 and 60 individuals). They obtained food by hunting (mostly the work of men); gathering fruits, vegetables, and roots (mostly the work of women); and scavenging. Our ancestors appear to have been mildly polygynous, with male–male competition focusing on access to females and females leaving their natal group to “marry” and giving birth every 4 or 5 years (see Bjorklund & Pellegrini, 2002; Kaplan et al., 2000). The climate in Africa during this time was variable, meaning that ancient humans had to be able to adapt to a wide range of ecological conditions (Potts, 1998). Evolutionary psychologists believe that selection pressures in such environments shaped many of the evolved human characteristics that are of particular interest to behavioral scientists, such as language, theory of mind, sophisticated tool use, and culture. Many of the adaptations that humans possess, however, have their origins in time periods that substantially predate the Pleistocene era. For example, the mechanisms underlying human attachment and sociality have long evolutionary histories as part of our more general primate and mammalian heritage (Foley, 1996). Furthermore, some evolution has also occurred in the past 10,000 years, as is reflected in population differences in disease susceptibility, skin color, and so forth (Irons, 1998). Although contemporary humans face many of the same problems faced by our ancestors (especially in the social realm), changes in material culture have produced environments radically different from those in which our ancestors lived and human minds evolved. After all, for over 99% of our history as a species, we lived in Pleistocene physical and social environments, without reading, writing, metal tools, or agriculture. Indeed, back on the Pleistocene savanna there were no fast food outlets, Botox injections, antibiotics, dating advertisements, jet airliners, and the like. Given such manifest changes in our environment and ways of living, one would expect much of human behavior to prove odd and maladaptive, as cognitive mechanisms that evolved under ancestral conditions struggle with the many new contingencies of the modern world (Durrant & Ellis, 2003). An assumption of evolutionary psychology, therefore, is that mismatches between modern and ancient environments often result in dysfunctional behavior (such as overconsumption of chocolate ice cream, television soap operas, video games, and pornography). Real-life examples of this phenomenon are easy to

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find. Our color constancy mechanisms, for instance, evolved under conditions of natural sunlight. These mechanisms fail, however, under some artificial lighting conditions (Shepard, 1992). Similarly, the dopamine-mediated reward mechanisms found in the mesolimbic system in the brain evolved to provide a pleasurable reward in the presence of adaptively relevant stimuli such as food or sex. In contemporary environments, however, these same mechanisms are subverted by the use of psychoactive drugs such as cocaine and amphetamines, which deliver huge dollops of pleasurable reward in the absence of the adaptively relevant stimuli, often to the user’s detriment (Nesse & Berridge, 1997). 4. Modularity Another assumption of evolutionary psychology is that most evolved cognitive mechanisms are domain-specific and modular in nature (e.g., Tooby & Cosmides, 1992, 2005). That is, humans (and other animals) did not evolve a “general intelligence” to be applied to whatever ecological conundrum they happen to face. Rather, what evolved are information-processing mechanisms crafted by natural selection to be sensitive to a particular range of stimuli and to solve specific survival-related problems. In the words of Steven Pinker (1997): “The mind is organized into modules or mental organs, each with a specialized design that makes it an expert in one area of interaction with the world. The module’s basic logic is specified by our genetic program. Their operation was shaped by natural selection to solve problems of the hunting and gathering life led by our ancestors in most of our evolutionary history” (p. 21). Such evolved cognitive mechanisms are sensitive to differences in environment for their eventual expression, but are universal and inherited by all biologically normal members of the species. Although modularity is a canon of evolutionary psychological explication, alternative proposals have been offered for the evolution of more domain-general abilities (e.g., Bjorklund & Pellegrini, 2002; Bjorklund & Rosenberg, 2005; Chiappe & MacDonald, 2005; Geary, 2005). Indeed, it is likely that different mechanisms vary in their levels of specificity and that there are some higherlevel executive mechanisms that function to integrate information across more specific lower-level mechanisms. We return to the issue of domain-general mechanisms, particularly Geary and Huffman’s (2002) concept of “soft modularity,” later in the chapter. As an example of modular evolved cognitive mechanisms, consider BaronCohen’s (1995, 2005) model of the development of theory of mind. Theory of mind refers to the understanding of how the mind works, particularly the knowledge that one’s behavior is determined jointly by what one believes or knows and by what one desires or wants (i.e., belief–desire reasoning, Wellman, 1990). This is especially critical in human psychological functioning; people who understand that their own behavior is governed by their beliefs and desires are also aware that other people have their own (sometimes different) sets of beliefs and

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desires (what Baron-Cohen refers to as “mindreading”). Successfully navigating the social terrain in a human group necessitates that one be able to take the perspective of another—to realize that the knowledge and/or motivations of others may not be identical to one’s own—and to behave accordingly. This is critical to compete effectively as well as for successful cooperation and for the efficient transmission of information through teaching. Baron-Cohen proposed four domain-specific modules, each of which was shaped by natural selection to solve specific adaptive problems encountered by our ancestors. These interacting modules have different developmental timetables and, together, are hypothesized to account for the development of mature belief–desire reasoning (see also Leslie, 1994). The earliest developing module is the intentionality detector, which interprets moving objects as having some “intention” toward the individual (e.g., that object intends to bite me, or to feed me, or to groom me). The intentionality detector is seen in human infants by 9 months of age. Also developing early in humans (about 9 months) is the eye-direction detector module, which detects eye-like stimuli, determines where the eyes are looking (at one’s self or at an object), and infers that if the eyes are looking at something the individual “sees” that thing. In other words, with the possession of the eyedirection detector module, one knows that knowledge is gained through the eyes. Perhaps somewhat surprisingly given the social-learning abilities of chimpanzees (P. troglodytes) and their cross-generation transmission of nongenetic information (e.g., forms of greeting, grooming, tool use; see Whiten et al., 1999), there is debate about whether these animals possess the eye-direction detector module (see Hare et al., 2000 for positive evidence and Povinelli & Eddy, 1996 for negative evidence). The third module, the shared-attention mechanism, is involved in executing and interpreting triadic interactions and representations. Unlike dyadic interactions and representations, triadic interactions and representations are concerned with embedding and recursion (Baron-Cohen, 2005). For example, if a mother is looking at a bottle and an infant can see the mother’s eyes and can see the bottle, then the infant can conclude, “Mom and I are looking at the same thing.” Similarly, this module may play a crucial role in social learning. For example, if a mother and baby are playing at a local playground and the baby witnesses another baby become frightened at seeing and hearing a barking dog, this baby may in turn conclude that his or her cohort is afraid of this dog and that barking dogs are things to avoid. This module, critical for referential communication, develops between 9 and 14 months of age. Finally, the theory-of-mind mechanism is roughly equivalent to the belief–desire reasoning described earlier and develops between the ages of about 18 and 48 months, culminating with the passing of false-belief tasks (see Wellman, Cross, & Watson, 2001). In one version of these tasks, a child and a confederate watch as an

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item is hidden in one location (A). The confederate then leaves the room and the experimenter or the child moves the object to a second location (B). The child is then asked where the out-of-the-room confederate will think the object is hidden. Most children 4 years of age and older state correctly that the confederate, being unaware that the object was moved, will look in location A, where the object was originally hidden. That is, the confederate will have a false belief. Most younger children state that the confederate will look in location B, where the object actually is. Such children, lacking the theory-of-mind mechanism, fail to attribute a false belief to the confederate. Baron-Cohen’s proposed modules for theory of mind follow a pattern of development consistent with Geary and Bjorklund’s (2000) set of predicted developmental features of evolved cognitive mechanisms. First, modules are hierarchic in nature, with the degree to which submodules are specialized being inversely related to their level in the hierarchy. For example, following Geary’s (1995, 2005) proposed domains of mind, the eye-direction detector is more specialized and subordinate to a more general theory-of-mind mechanism, which is subordinate to psychological mechanisms evolved to deal with conspecifics, which themselves are subordinate to more general psychological mechanisms dealing with social stimuli (at both the individual and the group levels). Second, there should be sensitive periods for the development of these abilities, and child-initiated activity should play a significant role in the emergence of these skills. Third, these mechanisms should be based on implicit knowledge/cognition (i.e., they are out of conscious awareness of the individual). The degree to which these mechanisms are executed automatically and without conscious awareness may be inversely related to their position in the hierarchy, with individuals being more likely to gain explicit awareness of the output of higher-level models. (Note that explicit awareness is likely unique to humans, whereas the other predicted developmental features should characterize nonhuman species as well.)4 Evidence in support of Baron-Cohen’s theory comes from people who seem to lack the latter two modules, the shared-attention and theory-of-mind mechanisms. High-functioning individuals with autism and people with Asperger’s syndrome, while often performing well on tasks involving nonsocial cognition, perform notoriously poorly on tasks involving the shared-attention or theory-of-mind mechanisms (e.g., Baron-Cohen, Leslie, & Frith, 1985; Baron-Cohen et al., 1999; 4

The argument that theory of mind is governed by a set of universal, monomorphic, modules does not imply that other domain-general mechanisms, such as executive function, may not also be involved in its development (e.g., Carlson, Moses, & Breton, 2002; Hughes, 2002; Perner & Lang, 2000; Sabbagh et al., 2006). These modules require input from the environment and may require development of more domain-general mechanisms for their proper function. In fact, we have argued previously that the evolution of domain-general inhibition abilities in human cognitive evolution was likely necessary before more domain-specific abilities associated with theory of mind and other aspects of social cognition could evolve (Bjorklund & Harnishfeger, 1995; Bjorklund & Kipp, 2002).

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see Baron-Cohen, 2005, for review). Additionally, people with autism have been shown to display neural deficits in the left frontal brain region, an area that has been associated with processing on theory-of-mind tasks for normal adults (e.g., Sabbagh & Taylor, 2000). B. DEVELOPMENTAL SYSTEMS THEORY Developmental systems theory puts forth a fully bidirectional account of organism–environment interaction: Development necessarily involves the continuous and bidirectional interaction between the individual at multiple levels of organization (e.g., genetic, neural, behavioral) and the environment at multiple levels (e.g., biochemical, physical, social) over time. At the core of developmental systems theory is the concept of epigenesis, defined as “an emergent process by which an organism’s structure and function change from relatively undifferentiated states to increasingly specialized, differentiated forms throughout ontogeny” (Miller, 1998, p. 105). Epigenesis involves the action of genes, of course, but also the action of RNA, proteins, neurotransmitters, neurons, and so on, all in interaction with the “environment,” broadly defined. Central to the concept of epigenesis is the activity of the organism itself in influencing its own development. According to Oyama (2000), “Fate is constructed, amended, and reconstructed, partly by the emerging organism itself. It is known to no one, not even the genes” (p. 137). 1. Probabilistic Epigenesis Gottlieb (1998, 2002; see also Ho, 1998) identified two types of epigenesis: predetermined and probabilistic. In predetermined epigenesis, which reflects the “central dogma” of molecular biology, activity can be thought of as unidirectional: genes
structure
activity. Probabilistic epigenesis, in contrast, is bidirectional in nature: genes  structure  activity  environment. In this system, each level of the organism (e.g., genetic, neural, behavioral, social) is influenced by, and interacts with, each adjacent level. This bidirectionality of structure and function has the capability of generating adaptive change for natural selection to act upon. Gottlieb (1998) notes that these adaptive changes (i.e., phenotypes) “are products of individual development and thus are a consequence of the adaptability of the organism to its developmental conditions. Therefore, natural selection has preserved (favored) organisms that are

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adaptively responsive both behaviorally and physiologically to their developmental conditions” (p. 796). Developmental systems theorists argue against any form of preformationism, the belief that some features of the organism exist in some form before their development into phenotypes. For example, developmental systems theorists argue that postulating “genes for” a particular trait, as evolutionary psychologists sometimes do, represents a form of preformationism. Instead, developmental systems theorists contend that all development results from “interactions of the components of complex systems” (Thelen & Smith, 1998, p. 564), beginning at the genetic level (genes are turned on or off or express different products depending on their current biochemical environment), through the structural level (neurons generate synapses, get organized with other neurons depending on the firing of neighboring neurons), to the environmental level (neurons fire as a result of stimulation from the external world). Feedback occurs between adjacent levels (e.g., not only do gene products influence the generation of structure, such as neurons, but also the activity of the structures, in turn, influences the subsequent activity of the genes). The result is the continuous interaction between structure (e.g., genes, neurons), function (i.e., activity emanating from structures), and exogenous environmental factors at all levels of organization. No structure or function in an organism is preformed (i.e., innate), waiting only for the proper environment for its activation; rather, structure and function emerge as a result of the continuous and dynamic interaction between adjacent levels of biological and environmental organization over time. From this perspective, genes are not seen as supplying “instructions” that are carried out by cellular machinery, or even information in the traditional sense. Genes have “developmental meaning” only when considered in relation to the larger developmental context (Oyama, 2000). 2. Epigenesis and the Emergence of “Instinctive” Behavior As an illustration of developmental systems, consider the phenomenon of imprinting in precocial birds, long a hallmark of “instinctive” behavior expressed in young animals during a critical point in development when exposed to the proper stimuli (e.g., Lorenz, 1937). Such traits were purportedly “hard-wired” into the genome, requiring little or no environmental input for phenotypic expression. Yet, experience during embryonic development is necessary for animals to display the species-typical behaviors, questioning the very notion of innate as “no experience necessary.” Following Kuo (1976), Gottlieb (1991, 1997) developed a procedure whereby ducklings, still in their eggs, had their vocal cords treated in such a way that prevented them from vocalizing. These ducklings were also isolated from their mothers, as well as from other prehatchlings. As a result, they did not hear the vocalizations characteristic of their species. Once hatched, the ducklings were put in a circular container with speakers on opposite sides, one that played the maternal call of their own species and

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one that played the call of another species. Ducklings with species-typical development—that is, hearing the vocalizations of their mother and conspecifics, as well as their own—approached the speaker that played the maternal call of their own species. In contrast, Gottlieb found that “treated” ducklings showed no significant preference for either call, demonstrating the role of prehatching auditory experience on subsequent attachment behavior. In all but the most exceptional circumstances, embryonic precocial birds hear the vocalizations of their mothers, their broodmates, and themselves. Exposure to these vocalizations is a critical component of the developmental system that reliably generates species-typical behavior (in this case, approaching the call of a conspecific) after hatching. This system structures the development of relevant neuronal circuits and sensory organs and is constrained by the organized relations between genetic, developmental, and environmental factors. Natural selection is a parsimonious process, and nothing more will be built into the genotype than is needed to achieve the functional outcome reliably in the context of the overall developmental system. Thus, we need not postulate a genetic program “for” imprinting. Rather, as Bjorklund and Ellis (2005) stated, “this genetic information is extensively scaffolded by species-typical features of the environment, and the phenotypic outcome is a predictable, emergent property of the total developmental system” (p. 13). 3. Developmental Timing, Experience, and the Ontogeny of Species-typical Behavior In all vertebrates, the senses mature in a common order, with neural areas associated with audition developing before those associated with vision (see Gottlieb, 1971). This pattern of brain development is correlated with perceptual experiences, with animals being exposed to auditory stimuli prior to visual stimuli. For example, although audition is not fully developed until after birth, mammalian fetuses’ auditory organs and associated brain regions are able to process sounds, with this ability increasing over the prenatal period. Early during prenatal development, the human fetus can likely distinguish circulatory and gastrointestinal noises, such as the mother’s heartbeat and stomach rumblings, whereas later in prenatal development the fetus is able to hear sounds from outside the womb, including the mother’s voice (see Turkewitz, 1993). There is no opportunity to see patterned light for either birds or mammals before birth, although fetuses may experience some diffuse light through their eggshell, for birds, or through their mother’s abdomen, for mammals. A number of theorists have argued that the brain develops in part via competition over neurons. For instance, in Edelman’s (1987) theory of neural Darwinism, neurons are in constant competition with one another, each attempting to recruit contiguous neurons to its group to perform a particular function (vision, for example). Groups of neurons that receive substantial stimulation (often in the form of internally generated activity) recruit more neurons than neuronal groups that receive less stimulation, resulting in canalization of neural systems. Thus,

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because different groups are constantly competing for the same cells, changes in patterns of activation can result in changes in brain organization (see Greenough, Black, & Wallace, 1987; Johnson, 1998, 2000; Nelson, 2001 for similar arguments). The coordination of sensory and brain development with perceptual experiences results in brain development proceeding for one system (e.g., audition) without competing for neurons with another system (e.g., vision) (Turkewitz & Kenny, 1982). When animals receive stimulation from one modality earlier than “expected” (i.e., when neural development and sensory experiences are uncoupled), it interferes with this choreographed dance between gene-influenced neural maturation and perceptual experience. This change in the gene–environment relation (in this case, a change in timing of different perceptual experiences) causes a species-atypical pattern of development. Research by Lickliter (1990) illustrates the role of developmental timing of sensory experience on perceptual development. Lickliter (1990) developed a procedure whereby bobwhite quails were exposed, by cutting holes in the eggs near the head, to patterned light 2–3 days prior to scheduled hatching. One to two days after hatching, the quails were placed in a round container with speakers on either side; one speaker played the maternal call of their own species, while the opposing speaker played the maternal call of a chicken. The control group consisted of quail chicks that had their shells cut open in the same location but were not exposed to patterned light. As one would expect, these control quails displayed species-typical behavior, consistently approaching the maternal call of their own species. The group exposed to patterned light, however, either showed no preference (25 of 44 animals) or displayed a preference for the maternal call of the chicken (7 of 44 animals). They did, however, show enhanced visual discrimination abilities compared to control birds. Numerous other studies have reported alterations in species-typical behavior in precocial birds as a result of early species-atypical experience (e.g., Columbus & Lickliter, 1998; Gottlieb, Tomlinson, & Radell, 1989; Lickliter & Hellewell, 1992; Lickliter & Lewkowitz, 1995; McBride & Lickliter, 1993; Sleigh, Columbus, & Lickliter, 1998). Presumably, sensory experience received earlier than is normative or in excess of species-typical levels interferes with development of neural circuitry associated with the later-developing sense, yielding often deleterious patterns of functioning. Such effects, moreover, are not limited to birds but have been observed in mammals as well (e.g., extra visual stimulation interferes with olfaction in rats, Kenny & Turkewitz, 1986; see Spear, 1984, for further discussion of the effects of too-early perceptual stimulation on rats). In fact, premature human infants, exposed to a host of tactile, auditory, and visual stimuli months before the brain “expects” such stimulation, display not only perceptual and cognitive impairments, as one might anticipate from a tooearly entry to the outside world, but also pockets of exceptional abilities and accelerated development (Als, 1995), reminiscent of Lickliter’s bobwhite quails.

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In sum, research on neural competition and developmental timing of sensory experience demonstrates the profound influence of experience on development of the most fundamental, species-typical traits, such as the neural architecture of auditory, visual, and olfactory systems. At the same time, however, these influences are part of a complex developmental system, of which genes are an indispensable component. Indeed, the effects of developmental experience are organized and constrained by a foundation of gene-influenced neural connections, which are often laid down in early development (see Black, 2003).

C. SUMMARY OF THE MAJOR ASSUMPTIONS OF EVOLUTIONARY PSYCHOLOGY AND DEVELOPMENTAL SYSTEMS THEORY The central tenet of evolutionary psychology is that adaptive behavior is predicated on adaptive cognitive processes—instantiated in evolved cognitive mechanisms—that were shaped by natural selection to deal with recurrent problems faced by our ancestors. The primary focus of evolutionary psychology is on species-universals; individual differences receive less attention. A guiding assumption of the field is that selection pressures encountered in ancestral environments shaped contemporary adaptations. For humans over the past 2 million years or so, these environments were characterized by life in small nomadic groups, hunting and gathering food, with a sexual division of labor, and a mildly polygynous mating system. The modern human mind is largely adapted to these ancestral environments, which sometimes produces behavior at odds with contemporary culture. Canonical evolutionary psychology asserts that the mind is composed of sets of domain-specific (modular) mechanisms, each shaped by natural selection to deal with specific adaptive problems. The central tenet of developmental systems theory is probabilistic epigenesis, which conceptualizes development as occurring via the bidirectional interaction between genes and environment at all levels of organization (genetic, neural, physical environment, social environment). Developmental systems theorists contend that no individual component of the developmental system determines phenotypic development. Instead, each component of the system interacts with other components at multiple levels of organization, and phenotypes emerge through this continuous and dynamic interaction. Accordingly, there is no preformationism (or “genes for” behavior). And even behaviors once thought to represent “instincts,” such as imprinting in precocial birds, can be conceptualized as the products of developmental systems that coordinate interactions between gene-influenced neural connections, timing of sensory/brain development, and experience. On initial inspection, these two theoretical approaches appear to be concerned with different phenomena and different levels of analysis. In fact, mainstream

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evolutionary psychology generally has paid only lip service, at best, to development, focusing instead on behaviors of adults. This makes sense to the extent that it is the adults of a species that do the reproducing and child rearing, the sine qua non of evolutionary explication. But individuals must survive infancy and childhood before they reach adulthood, and we and others have argued that evolutionary psychology needs to consider more seriously issues of development (Bjorklund & Ellis, 2005; Bjorklund & Pellegrini, 2000). It is at this junction that evolutionary psychology and developmental systems theory interact (some may say collide), and in the next section we examine the perceived incompatibilities of these two theoretical (or meta-theoretical) approaches.

III. What is the Perceived Incompatibility of Evolved Cognitive Mechanisms and Probabilistic Epigenesis? Until recently, the paths of evolutionary psychologists and developmental systems theorists rarely crossed; each group pursued its research agenda without giving much thought to the other. As developmental psychologists became increasingly interested in evolutionary psychology on the one hand, and as evolutionary psychology gained in prominence in academic circles on the other hand, it became inevitable that each discipline would have to acknowledge and engage the other. As we have seen in the previous section, both evolutionary psychology and developmental systems theory are concerned with how genes and environments interact during ontogeny to produce competent adult behavior. However, the core concepts of the two disciplines are seemingly at odds as to how this occurs. Developmental systems theorists accuse evolutionary psychologists of practicing a form of genetic determinism (e.g., Lickliter & Honeycutt, 2003), whereas evolutionary psychologists argue that developmental systems theory posits a nearly infinite degree of behavioral plasticity and, as a result, the theory has no ability to predict species-typical patterns of behavior (e.g., Tooby, Cosmides, & Barrett, 2003). The following sections examine these perceived incompatibilities.

A. CLAIMS OF GENETIC DETERMINISM AND UNREALISTIC PLASTICITY According to some proponents of developmental systems theory (e.g., Lickliter & Honeycutt, 2003; Moore, 2001; Oyama, 2001), the notion of evolved cognitive mechanisms implies a form of genetic determinism, or preformationism. This is attributed to developmental systems theory’s more expansive view of what evolves. According to developmental systems theorists, what evolves are

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not “cognitive mechanisms” or even “genes,” per se, but developmental systems, of which genes are a critical part. According to Oyama (2000, p. 29): What is transmitted between generations is not traits, or blueprints, or symbolic representations of traits, but developmental means (or resources, or interactants). These means include genes, as previously stated, may include a maternal reproductive system, parental care, or other interaction with conspecifics, as well as relations with other aspects of the animate and inanimate worlds. This context, which is actually a system of partially nested contexts, changes with time, partly as a result of the developmental processes themselves.

Accordingly, a developmental system includes both genome and environment. From this perspective, there is nothing “innate” in the genes that dictates the formation of cognitive adaptations. Development proceeds via a probabilistic process, with the eventual adult phenotype being the product of continuous and complex interactions over the course of ontogeny. Although genes play an integral role in both development and evolution, that role is fully integrated into the larger developmental system. Most evolutionary psychologists bristle at the charge of genetic determinism, claiming that their opponents misunderstand or distort their views (e.g., Buss & Reeve, 2003; Tooby et al., 2003). With respect to genes that underlie evolved cognitive mechanisms, evolutionary psychologists emphasize that genes do not cause behavior and cognition directly. Rather, through their role in regulating cell number, neuron migration, shape and connection of individual cells, the microstructure of molecules surrounding synapses, and so forth, genes help build the foundation that underpins the design of evolved cognitive mechanisms, and this foundation predictably interacts with nongenetic factors during development to reliably produce species-typical phenotypes (anatomical, physiological, and behavioral). We have argued previously that the misperception of evolutionary psychologists as genetic determinists is due in part to evolutionary psychology’s lack of a developmental model for explaining how inherited genetic information becomes expressed in the adult phenotype (e.g., Bjorklund & Ellis, 2005; Bjorklund & Pellegrini, 2000, 2002; Hernández Blasi & Bjorklund, 2003). Moreover, although we believe that developmental systems theory’s account of how genes and environment interact to produce unique individuals is largely accurate, the dynamic nature of and high degree of plasticity in ontogeny posited by developmental systems theorists make the specific path that ontogeny will take for any individual nearly impossible to predict. In fact, as we commented earlier, this has been a central criticism by evolutionary psychologists raised against developmental systems theory (e.g., Burgess & MacDonald, 2005; Buss & Reeve, 2003; Tooby et al., 2003). Developmental systems theory must explain how different members of the species end up resembling one another, and how development for any individual is a generally predictable phenomenon, without postulating anything preformed in the genes. Developmental systems theory’s simple answer is that individuals inherit both a species-typical genome and a species-typical environment that

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interact predictably, albeit in a dynamic way, over the course of ontogeny (e.g., Bjorklund & Pellegrini, 2002; Oyama, 2000). Indeed, many species-typical adaptations are virtually universal (e.g., the architecture of the visual cortex, mammalian stress response systems). In such cases, the nature of gene–environment interactions is highly structured. The types of environmental information that the genes depend on are virtually always present in a species-typical developmental environment (e.g., gravity, humidity, patterns of light, prehatching exposure to conspecific vocalizations). These nonvarying environmental inputs interact with an underlying monomorphic genetic structure in a predictable manner. The resulting developmental process reliably produces the phenotypic outcome or adaptation. For example, imprinting in precocial birds (discussed previously) and children’s universal acquisition of language (discussed later) develop so reliably that they have at times inspired the labels “innate” or “hard-wired.” In actuality, the reliable, species-typical natures of auditory imprinting and language acquisition are due to the fact that critical components of their corresponding developmental systems, including relevant genes and nongenetic factors in the environment, are largely unvarying. Consistent with evolutionary psychology’s approach to evolution and development, natural selection has operated to reduce both genetic and experiential variability within certain domains, resulting in reliably developing, species-universal features. However, consistent with developmental systems theory’s account of the dynamic and fully bidirectional nature of gene ⫻ environment ⫻ development interactions, species-typical developmental outcomes are achieved through probabilistic epigenesis. This inheritance of structured gene–environment relations extends to the biochemical level. The activity of genes is dictated by the cellular environments in which they are located and the stimulation those cells receive, either from other cells/tissues or, especially for neurons, from sources external to the body (Johnston & Edwards, 2002). Genes are actively involved in all aspects of development and, in fact, all aspects of behavior and cognition; but they do not influence complex behavior directly, only through the proteins they cause to be synthesized and the effects those proteins have on the cells they reside in (or comprise). It is the relations among cells—most importantly of neurons for our purposes—that influence behavior, and these effects emerge dynamically. Nonetheless, the dynamic relations between neurons and species-typical sources of stimulation have been structured by natural selection to produce predictable patterns of development; accordingly, the developing organism can be said to “expect” certain configurations of stimulation similar to those their ancestors experienced (cf. experience-expectant development; Greenough et al., 1987) and to be “prepared” for certain types of experiences or relationships. We realize that the use of such terms as “expectation” and “preparedness” are anathema to developmental systems theorists because they view such terms as

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implying an implicit association with preformationism. This is an association that we neither intend nor perceive. From our perspective, this does not contradict the concept of probabilistic epigenesis (although we recognize that it is not in accordance with a strict constructivist interpretation of developmental systems theory). As articulated later in this chapter, the developmental concepts of expectation and preparedness afford an opportunity for a rapprochement between probabilistic–epigenetic perspectives and evolutionary psychology.

B. EXPLAINING PHENOTYPIC PLASTICITY Whereas the development of all adaptations depends on various regularities in the environment, the development of many adaptations also depends on systematic (structured) variation in the environment. That is, for many adaptations, the types of environmental information that interact with underlying genes vary substantially within species-typical environments (as do, for example, diet, quality of parental investment, social competition, and mortality rates). When, over evolutionary time, the fitness of alternative phenotypes is predictable on the basis of observable environmental cues, natural selection tends to favor phenotypic plasticity: neural circuits that reliably guide development of alternative phenotypes (anatomical, physiological, behavioral) in response to given ecological or developmental conditions (see Pigliucci, 2001; West-Eberhard, 2003). Adaptive phenotypic plasticity enables matching of the phenotype to conditions under which it is expressed. Most scientists and theorists concerned with these issues concur that phenotypic plasticity is constrained, occurring within boundaries of genetically inherited reaction norms (see Schlichting & Pigliucci, 1998), although the limits of such boundaries may not necessarily be known. Debate typically revolves around the degree of plasticity (or inversely, constraint) afforded by the genome, with proponents of developmental systems theory often minimizing the role of genetic constraints and maximizing the role of plasticity, whereas proponents of evolutionary psychology often take the opposing view. Both perspectives, however, concur that genes and environment cannot be simply partitioned but interact from the earliest stages of embryonic development throughout the life span (see Geary, 2005). Evidence that proponents of both developmental systems theory and evolutionary psychology use to support their views comes from species that develop in qualitatively different ways depending on environmental conditions, usually early in life. For example, the sex of many reptiles is determined by the temperature at which eggs are incubated; the morphology of certain caterpillars depends on what they eat during the first days of life; and some species of fish change sex (from female to male) depending on the presence of a reproductive male in the school (see Black & Grober, 2003; West-Eberhard, 2003).

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Developmental systems theorists view such plasticity as reflecting the potent role of the environment in the expression of genes (e.g., Gottlieb, 1998), a clear indication that genes, in and of themselves, do not determine phenotypes. Yet evolutionary psychologists and biologists note that the different phenotypes expressed in these examples are not random, but were themselves shaped by natural selection (e.g., Belsky et al., 1991; Gross, 1996; Rhen & Crews, 2002). For example, summer broods of the caterpillar Nemoria arizonia feed on oak leaves and develop morphology that resembles twigs, which serve as camouflage against the summer foliage; the spring brood feeds on oak catkins and develop the appearance of oak flowers, enabling them to blend into the spring floral environment (Greene, 1996). The caterpillars, therefore, predictably and adaptively match their phenotypes to the floral conditions under which they are expressed. In describing phenomena such as the different morphs of N. arizonia in response to early diets, Boyce and Ellis (2005, p. 290) employ the concept of conditional adaptations, defined as: … evolved mechanisms that detect and respond to specific features of childhood environments—features that have proven reliable over evolutionary time in predicting the nature of the social and physical world into which children will mature—and entrain developmental pathways that reliably matched those features during a species’ natural selective history. Conditional adaptations … underpin development of contingent survival and reproductive strategies and thus enable individuals to function competently in a variety of different environments.

Conditional adaptations can evolve only when the fitness of alternative phenotypes is predictable on the basis of reliable cues that can be observed by the individual. Relevant cues include both external environmental factors (e.g., physical resources, social crowding, parental reproductive strategies) and indicators of the individual’s status or relative competitive abilities in the population (e.g., age, body size, health, history of wins and losses in agonistic encounters) (Gross, 1996; West-Eberhard, 2003). The evolution of conditional adaptations requires development and maintenance of the necessary sensory and regulatory machinery—sensory organs, neural pathways, endocrine systems, genetic architecture—to detect and encode relevant cues and then respond to them in a timely manner (at least during developmental periods of phenotypic readiness to respond). The concept of conditional adaptations differs from the view of developmental systems theory on at least one major dimension: gene-driven processes. That is, the necessary architecture for conditional adaptations is a reliably developing part of the organism that exists in some form (in genetic coding for neural systems) before its development into phenotypes. The conditional adaptation concept assumes systematic relations between genes and environment that were structured by natural selection. These gene–environment interactions reliably generate species-typical neural circuits, and these circuits form the basis of environmentally sensitive

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regulatory mechanisms that enable the organism to adaptively and predictably adjust developmental trajectories. Consider the example of age at menarche in girls. Drawing on life history theory, various evolutionary biologists and psychologists (e.g., MacDonald, 1999; Miller, 1994; Surbey, 1998) have argued that in K-selected species (those characterized by high-investment/low-fertility reproductive strategies, such as humans) scarcity of resource should be negatively correlated with rate of sexual maturation. These theorists posit that members of the human species, under conditions of chronically low energy availability, are primed to delay maturation and reproductive viability until predictably better times (see also Wasser & Barash, 1983). The core argument is that natural selection has favored physiological mechanisms (i.e., it has conserved developmental systems, including genetically influenced neural connections) that track variation in resource availability and alter gene expression in response to this variation. This systematic interaction between environmental conditions and gene expression functions to entrain physical development to match resource availability. Consistently good conditions in early and middle childhood signal to the individual that accelerated development and early reproduction are sustainable. Conversely, conditions of resource scarcity cause the individual to reserve energy for maintenance and survival (rather than growth or reproduction).5 There is now compelling evidence that children who experience chronically poor nutritional environments grow slowly, experience late pubertal development, and achieve relatively small adult size, whereas children who experience chronically rich nutritional environments grow quickly, experience early pubertal development (relative to their genetic potential), and achieve relatively large adult size (Ellis, 2004; Ellison, 2001). These data are consistent with the conditional adaptation model and indicate that children adaptively and predictably adjust physical development to match ecological conditions. Nonetheless, there could be a simpler “absence of impairment” explanation for the data. The absence of impairment hypothesis posits that, given sufficiency of resources and absence of biological insults, organisms achieve their full developmental potential (e.g., fast growth, large body size) (Worthman, 1999). The completeness of the absence-of-impairment hypothesis has been strongly challenged by Worthman, however, who presents several lines of evidence demonstrating that absence of impairment does not influence pubertal timing in a simple linear or unidirectional manner. For example, poor children adopted from Third World countries into affluent Western families experience significantly earlier puberty than do children from either their countries of origin or their host 5

It is important to note that psychosocial stress (as opposed to nutritional or energetic stress) has often been found to accelerate pubertal development. The theoretical bases and empirical evidence regarding the contrasting effects of physical and psychosocial stress on pubertal development are reviewed in Ellis (2004).

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countries, despite histories of infection and malnutrition prior to adoption (reviewed in Mul, Oostdijk, & Drop, 2002). Moreover, Indian and Bangladeshi girls adopted into Swedish families experience earlier menarche if they are adopted at later ages (mean age at menarche is 11.1 years for girls adopted at ⭓ 3 years of age and 11.9 years for girls adopted at ⬍ 3 years of age; Proos, Hofvander, & Tuvemo, 1991), even though the older adoptees experienced more sustained deprivation prior to adoption. Consistent with the adaptationist framework positing evolved physiological mechanisms that track energy availability, Worthman (1999) states “the life history model would predict that girls experiencing persistent deprivation would react to a dramatic improvement in environmental quality by hastening reproduction in order to exploit a narrow window of resource availability” (p. 141). Developmental systems theorists view the concept of conditional adaptation as reflecting a form of “prespecification,” with organisms “foreseeing” which of a few prespecified alternative developmental pathways they will take, depending on ecological factors (Nelson, 2005). That is, developmental systems theorists reject the assumption, commonly held by evolutionary psychologists, that conditional adaptations are instantiated in the inherited architecture of the brain, exist in some form prior to individual development, and are then activated in ontogeny by specific experiences or features of species-typical environments (cf. the Greenough et al. (1987) concept of experience-expectant development, discussed briefly earlier). Developmental systems theorists emphasize that there is no prespecification of traits or characters and that all developmental outcomes are achieved or “generated” in the dynamics and processes of individual ontogeny (see Oyama, Griffith, & Gray, 2001). Although we concur that all traits are generated in ontogeny, phenotypes are constrained by genes, experience, and their interactions, making some outcomes more probable than others. In the case of conditional adaptations, a limited range of phenotypes, each matched to a delimited environmental condition, have evolved. Developmental systems theory fails to address how the range of alternatives becomes limited (as in the two morphs of N. arizonia, for example), if not via some genetic “prespecification.” Gene ⫻ environment ⫻ development interactions have been structured by natural selection, yielding only two viable morphological adaptations in N. arizonia. Although developmental plasticity and natural selection may work to generate new alternatives in the future, conditional adaptations refer to adapted solutions of contemporary species that have evolved a restricted range of outcomes, dependent on environmental conditions. In sum, developmental systems theorists view evolutionary psychological explanations, such as conditional adaptations, as affording undue influence to genes in producing behavior, whereas evolutionary psychologists view developmental systems explanations as all but ignoring genes in explaining the emergence of behavior. Although each may be unwittingly criticizing a caricature of

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the other, the two disciplines seems to occupy opposite poles on the modern nature–nurture continuum, making a rapprochement impossible. Taking an average of these two perspectives with respect to explaining the emergence of adaptively structured adult phenotypes may be an intellectually impossible (and disingenuous) task; yet we do believe that each perspective provides valuable insight for explaining human behavior and that a middle ground is tenable. Such a middle ground, however, must be more than the mean of its constituent parts; it needs to reflect an integrated position itself. In the forthcoming sections we present a new approach to conceptualizing gene ⫻ environment ⫻ development interactions—evolved probabilistic cognitive mechanisms—that is born from the component parts of evolutionary psychology and developmental systems theory.

IV. Evolved Probabilistic Cognitive Mechanisms A. GENE ⫻ ENVIRONMENT ⫻ DEVELOPMENT INTERACTIONS We believe that the misunderstanding that exists between developmental systems theory and evolutionary psychology proponents can be reduced, if not resolved, by the introduction of a new concept: evolved probabilistic cognitive mechanisms. These are information-processing mechanisms that have evolved to solve recurrent problems faced by ancestral populations; however, they are expressed in a probabilistic fashion in each individual in a generation, based on the continuous and bidirectional interaction over time at all levels of organization, from the genetic through the cultural. These mechanisms are universal, in that they will develop in a species-typical manner when an individual experiences a species-typical environment over the course of ontogeny. That is, consistent with Brunswik’s (1955a, 1955b) theory of probabilistic functionalism, evolved probabilistic cognitive mechanisms make use of and depend on systematic information and relations in the ecological–environmental contexts in which development regularly and predictably occurs. However, these mechanisms are subject to modification in any particular individual as a result of perturbations in these contexts. Evolved probabilistic cognitive mechanisms are thus defined as cognitive mechanisms that are functionally organized to solve recurrent problems faced by ancestral populations, are highly probable when species-typical environments are encountered (i.e., when the developmentally relevant features of the environment are in the range typically encountered during a species’ evolution), and are products of emerging developmental systems that have evolved over the course of the ontogenies of our ancestors. Such a concept acknowledges that natural selection has operated to produce cognitive (and perceptual and behavioral) mechanisms that are well adapted to a species-typical environment, but that these mechanisms emerge through continuous and bidirectional gene ⫻ environment ⫻ development

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interactions and are thus modifiable when an organism experiences circumstances outside of the normal species range. From this perspective, evolved probabilistic cognitive mechanisms prepare an organism for life in a species-typical environment, but they are not preformed (Bjorklund, 2003). Consistent with the concept of evolved probabilistic cognitive mechanisms, Cummins and Cummins (1999, p. B45) write: Rather than assume that early emerging and specialized cognitive capacities are either innate or learned, we may suppose instead that organisms do not inherit modules fully formed, but have a biological preparedness (Seligman, 1971) to very quickly develop specialized cognitive functions for solving classes of problems that were critical to the survival and reproductive success of their ancestors.

Cummins and Cummins believe, and we concur, that the argument should not be over whether a cognitive (or physical) trait is innate. All traits are influenced jointly by genes and environment, making the concept of “innateness,” as traditionally understood, nonsensical. Furthermore, all genetic processes are sensitive to certain elements of the environment but not others. In general, the relation between genes and environment is highly structured, so that genes are expressed in a predictable (i.e., species-typical) way when exposed to particular speciestypical events, and the effects of experience on neural circuits are organized and constrained by genes. Similarly, Geary and Huffman (2002; see also Geary, 2005) offer a model of soft modularity, with cognitive systems emerging via the interaction of inherent constraints and patterns of experience over the course of (especially early) development. Consistent with the principal tenet of evolutionary psychology, Geary and Huffman propose that animals evolved domain-specific modules to deal with recurrent and relatively invariant aspects of ancestral environments. For instance, most visual abilities, although requiring patterned light for their proper instantiation, develop in a species-typical way under all but the most deprived conditions, as does a child’s ability to represent human faces. For such abilities, natural selection would have favored domain-specific, modular-like mechanisms, requiring only species-typical experiences for their proper establishment and development (cf. experience-expectant processes, Greenough et al., 1987). However, in addition to domain-specific modules, natural selection would have favored more domain-general processes, required for dealing with aspects of an animal’s environment that are more variable over situations, ontogeny, and generations. For humans, the judgments and decisions involved in avoiding predators, hunting, gathering, tool construction and use, finding and maintaining mates, child rearing, and dealing with conspecifics in general, among others, would be highly variable. To handle such tasks, one would be better served by developing mechanisms that are pliable and able to deal with the changing contingencies of an often unpredictable environment. This does not preclude the

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presence of constraints specific to a broader domain (e.g., social domain for dealing with conspecifics, engineering domain for tool use). In fact, such constraints exist, and it is an animal’s specific experiences in interaction with these constraints that yield adaptive behavior for these complex and variable problems. Consistent with the relation between plasticity and evolved probabilistic cognitive mechanisms proposed here, Geary and Huffman (2002) hypothesize that “the primary benefit of developmental plasticity is the ability to accommodate information patterns that have been variable during the species’ evolutionary history and that this variability largely results from dynamic interactions among biological organisms” (p. 681).

B. LANGUAGE DEVELOPMENT AND EVOLVED PROBABILISTIC COGNITIVE MECHANISMS Consider the example of language. Many of the language-acquisition processes proposed by neonativist theorists can be interpreted in terms of evolved probabilistic cognitive mechanisms. These theorists have contended that children are born with a universal grammar and a primitive knowledge of syntax and, over the course of the first 5 or 6 years of life, contrast their “innate” grammar with the language that surrounds them, modifying their theory of language as they do (see Pinker, 1994). Indeed, the early sentences of children around the globe are similar in construction and seem to reflect a common set of linguistic parameters, and the ways that children acquire various aspects of language (such as learning to use prefixes and suffixes) are similar regardless of the language they speak. Children around the world, moreover, acquire language following a universal timetable. These species-typical developmental processes are clearly underpinned by genetic information, but this information interacts with and is highly sensitive to a particular class of environmental input: spoken or signed language, perhaps expressed in an explicitly social context (e.g., Bruner, 1983). Importantly, the particular language that a child hears is irrelevant to fundamental processes of language acquisition, as are many other aspects of the environment, such as exposure to patterned light. Genes associated with language acquisition have evolved to be sensitive to a delimited range of environmental stimulation (or perhaps, more appropriately, to contribute to the development of brain structures sensitive to such stimulation), but not to stimulation outside that range. In total, language is the product of a uniquely human developmental system, and the nested gene ⫻ environment ⫻ development interactions that subserve this system are highly structured, making language acquisition, while not inevitable, at least highly probable and predictable within a species-typical linguistic environment.

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1. Developmental Timing Developmental timing is a well-studied topic in both developmental and evolutionary psychology. A key question is whether natural selection has shaped certain developmental systems to be more open to relevant environmental influences during certain “sensitive periods.” To that end, we posit that evolved probabilistic cognitive mechanisms are often time-dependent (Geary & Bjorklund, 2000). Genes and corresponding brain structures may be sensitive to particular aspects of the environment at some times in development but not others. With respect to language acquisition, there are several sources of evidence for a sensitive period, including (a) language deficits in children who were isolated or otherwise deprived of exposure to spoken language until later in life (e.g., Curtiss, 1977), (b) varying proficiency in acquisition of a second language as a function of age of exposure (e.g., Johnson & Newport, 1989), (c) age-linked recovery of function from damage to areas of the brain associated with the production or comprehension of language (e.g., Witelson, 1987), and (d) the predictable age of acquisition of sign language in deaf people (e.g., Newport, 1990). 2. Constrained Developmental Systems A core feature of evolved probabilistic cognitive mechanisms is that they are the products of constrained developmental systems. Consider the operation of evolved probabilistic cognitive mechanisms for language in a special group of children from a Nicaraguan school for the deaf. Both hearing and deaf babies begin to babble at about the same time. However, deaf babies eventually stop babbling verbally because, unlike hearing babies, they do not receive auditory feedback (Oller & Eilers, 1988), although deaf babies exposed to sign language may continue to “babble” with their hands (Petitto & Marentette, 1991). The deaf Nicaraguan children possessed no formal language (verbal or signed) before entering the school and sign language was not taught at the school. Nevertheless, over several cohorts of children a true language (Nicaraguan Sign Language) emerged, developed by the children themselves and possessing the structure observed in other true languages (Senghas & Coppola, 2001; Senghas, Kita, & Ozyürek, 2004). From this research, we can see that language is a complex system, with structure emerging from interactions of individuals attempting to communicate their desires and ideas with one another. In the absence of a community of other signers (in fact, several cohorts of signers), children remain vocally and manually mute; but even children who are not exposed to a previously established language will invent their own language given the proper social environment. Especially in domains such as these, when children inherit a highly constrained developmental system for a particular outcome (e.g., language acquisition), we can invoke the concept of evolved probabilistic cognitive mechanisms. There is likely a suite of such mechanisms underlying language development

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that are involved in identifying, filtering, storing, and processing relevant environmental stimuli with the aim of acquiring language.6 Yet, as noted previously, simply because a trait is highly probable does not mean that its development is impervious to atypical environments. Language development is highly dependent on environmental input, but it is dependent on a particular class of environmental input that the relevant set of genes (and corresponding brain structures) has evolved to interact with. So although language does not arrive preformed, the developing child is prepared to acquire language through selectively structured gene ⫻ environment ⫻ development interactions. C. PREPARED LEARNING Prepared learning offers other examples of a particular class of evolved probabilistic cognitive mechanisms. Rats associate nausea with previously consumed novel food, not with other environmentally present stimuli (e.g., Garcia & Keolling, 1966). Similarly, monkeys, rather than having an innate fear of snakes, easily acquire such fear via social learning, although they do not similarly learn to fear rabbits or flowers toward which they observe a conspecific reacting fearfully (e.g., Mineka et al., 1984). With respect to fears, we argue, following Seligman (1970, 1971), that humans and other animals have predispositions to acquire certain fears (e.g., of snakes) more easily than others (e.g., of rabbits) based on our species’ phylogenetic history, but these do not develop in the absence of experiential factors. This is accomplished in part by differential attention to potentially threatening stimuli. The selectively attentive feature of human cognitive architecture was demonstrated in a series of experiments by Öhman, Flykt, and Esteves (2001) in which college students viewed a 3 ⫻ 3 matrix composed of nine pictures. The matrices consisted of either fear-relevant items (e.g., spiders, snakes) against a background of fear-irrelevant items or fear-irrelevant items (e.g., mushrooms, flowers) against a background of fear-relevant items. Participants were to determine, as quickly as possible, whether the items in each array came from the same category (e.g., all flowers) or from different categories (e.g., flowers and snakes). Öhman et al. (2001) hypothesized that participants would display faster response times to matrices in which pictures of fear-relevant stimuli were presented against a backdrop of fear-irrelevant stimuli (e.g., spiders or snakes against a backdrop of mushrooms) than the reverse. The results from each experiment supported their hypothesis, demonstrating that humans attend 6

We say “with the aim of acquiring language” to mean that, over the course of human evolution, children who possessed these mechanisms and used them to acquire language experienced increased fitness. There is no need to posit that the developing organism is “purposely” learning language.

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more quickly to evolutionarily relevant stimuli than to nonevolutionarily relevant stimuli. Similar results using the visual-search paradigm have recently been reported for preschool children (LoBue & DeLoache, 2005; see also Rakison, 2005, for a similar conclusion based on a habituation/dishabituation paradigm with infants), suggesting that these are early developing learning mechanisms. Such selective attention to potentially dangerous animals is very likely part of a predator-avoidance adaptation, but the avoidance of neither dangerous animals nor potentially poisonous food is “innate,” at least not in the simplistic meaning of the term. As Wilson (1975) stated, “What evolves is the directedness of learning—the relative ease with which certain associations are made and acts are learned, and others are bypassed even in the face of strong reinforcement” (p. 70). Some types of stimuli are more likely to be detected, to be attended to, and to produce adaptive (i.e., fear) responses than others, and such constrained learning presumably emerges through prenatal and early postnatal development via the expression of sets of genes in species-typical environments. But evolved (and developed) learning mechanisms are products of selectively structured gene ⫻ environment ⫻ development interactions; they require specific experiences before they yield adaptive behavior, and should an animal not have such experiences, it will not display the species-typical pattern. Proposing that aspects of cognitive or social development are governed by evolved probabilistic cognitive mechanisms does not imply that we know, at this time, what those specific mechanisms are, which genes or which aspects of the environment are involved, or the particular nature of the gene ⫻ environment ⫻ development interactions. These remain empirical questions to be addressed in the context of specific lower-level theories and hypothesis. For example, theorists who propose that language is socially constructed through interactions between infants and adults (particularly mothers) may also have a significant part of the story right (Bruner, 1983; Carpenter, Nagell, & Tomasello, 1998; Tomasello, 2003). Some evolved probabilistic cognitive mechanisms involved in language acquisition may be sensitive to how language is presented to children as well as to the linguistic structure of the input. The specific nature of particular evolved probabilistic cognitive mechanisms needs to be determined. But that such universal and important aspects of development were structured by natural selection and that they can be explained only via mechanisms that take into consideration gene ⫻ environment ⫻ development interactions should not be questioned. The concept of evolved probabilistic cognitive mechanisms can be used by people of different theoretical persuasions to explore the detailed nature of ontogeny while sharing a common understanding that development is the product of gene–environment interaction that itself has an ancient and dynamic history.

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V. What’s in a Name? Evolutionary and developmental psychologists have often not seen eye-to-eye on the underlying causes of behavior, and these differing views can be attributed in part to the intellectual traditions from which the two disciplines trace their roots. Evolutionary psychologists are the inheritors of sociobiology and neo-Darwinism and have embraced the gene’s-eye view of life (e.g., Dawkins, 1976). Developmental psychologists, particularly those advocates of the developmental systems perspective, come from a history of emphasizing the effects of early experience on later behavior and the inherent plasticity of behavior early in development. The child is the father to man, and the particulars of experience early in life, even if they follow a species-typical pattern, shape the adult. But this is history, and proponents of both fields often go to great lengths to combat the impression of either genetic or environmental extremism. Each camp is aware of advances in genetics and recognizes both the potent role of genes in influencing structure and function and the simultaneous impotence of genes in the absence of appropriate environmental and developmental conditions. But the lens we peer through affects what we see and also how we describe it. As a result, developmental and evolutionary psychologists often talk past one another, and this is sometimes due to the language they use. Phrases such as “reliably developing,” “innate,” “emergence,” and “self-organization” often mean different things to evolutionary and developmental psychologists and usually go undefined. Practitioners of these different disciplines in psychology tend to write for their own tribe and, as a result, frequently misinterpret what members of the other tribe have to say. But when evolutionary psychologists do talk about development, they often describe it much as developmental systems theorists do. Consider the following statements from Tooby and Cosmides (1992), two of the architects of evolutionary psychology, discussing “Development from an Adaptationist Perspective”: It is this developmentally relevant environment—the environment as interacted with by the organism—that, in a meaningful sense, can be said to be the product of evolution, evolving in tandem with the organism’s organized response to it (p. 84). By changing either the genes or the environment any outcome can be changed, so the interaction of the two is always part of every complete explanation of any human phenomenon. As with all interactions, the product simply cannot be sensibly analyzed into genetically determined and environmentally determined components or degrees of influence. For this reason, everything, from the most delicate nuance of Richard Strauss’s last performance of Beethoven’s Fifth Symphony to the presence of calcium salts in his bones at birth, is totally and to exactly the same extent genetically and environmentally codetermined. ‘Biology’ cannot be segregated off into some traits and not others (pp. 83, 84).

From the other camp, there are card-carrying developmental psychologists who apply a probabilistic–epigenetic perspective (sometimes explicitly, sometimes

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not) to an evolutionary account of human development (e.g., Belsky, 2005; Bjorklund & Ellis, 2005; Bjorklund & Pellegrini, 2002; Bugental, 2000; Geary, 1998; Ploeger, van der Maas, & Raijmakers, in press; see Ellis and Bjorklund (2005) and Burgess and McDonald (2005) for examples of both developmental and evolutionary psychologists examining child development from an evolutionary psychological perspective). For example, in the conclusion of the article introducing the field of evolutionary developmental psychology, Geary and Bjorklund (2000) wrote: “A complete understanding of human social and cognitive development, and any associated sex differences, requires an understanding of human evolution and the associated epigenetic processes that guide the development of evolved social and cognitive phenotypes” (p. 63). Although many unresolved issues remain, both within and between developmental and evolutionary psychology, we think that some of the differences between the two camps are more apparent than real and that this is attributed, in part, to the lack of a common terminology. The concept of “evolved probabilistic cognitive mechanism” does not reflect a new discovery, merely a way of looking at gene ⫻ environment ⫻ development interaction and its relation with evolutionary change; but the concept’s explicit recognition of both the adaptive nature of inherited cognitive mechanisms and their probabilistic course, dependent on genetic and environmental constraints within a developmental system, should ring true to both developmental and evolutionary psychologists. We can argue about and research the nature of these constraints, the degree to which any particular developmental trajectory is subject to perturbation, and how genetic and environmental factors interact to yield any particular pattern of development and thus any particular adult phenotype. But advances in developmental science are more likely to be made when people stop talking past one another. Sometimes a new concept, which captures the essence (if not always the particulars) of a phenomenon, can help serve that cause.

Acknowledgments We thank Aurelio José Figueredo, Jay Belsky, and Annemie Ploeger for comments on earlier drafts of the manuscript.

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DEVELOPMENT OF EPISODIC AND AUTOBIOGRAPHICAL MEMORY: A COGNITIVE NEUROSCIENCE PERSPECTIVE

Nora S. Newcombe a, Marianne E. Lloyd b and Kristin R. Ratliff a a

DEPARTMENT OF PSYCHOLOGY, TEMPLE UNIVERSITY, PHILADELPHIA, PA 19122, USA DEPARTMENT OF PSYCHOLOGY, SETON HALL UNIVERSITY, SOUTH ORANGE, NJ 07079, USA

b

I. II.

DIFFERENTIATING INFANTILE AND CHILDHOOD AMNESIA ARCHITECTURE OF THE HUMAN MEMORY SYSTEM A. A MODERN TYPOLOGY OF LONG-TERM MEMORY B. WHAT IS AUTOBIOGRAPHICAL MEMORY?

III.

BRAIN BASES OF HUMAN MEMORY A. ROLE OF THE HIPPOCAMPUS IN EPISODIC AND SEMANTIC MEMORY B. ROLE OF THE FRONTAL LOBES IN EPISODIC AND SEMANTIC MEMORY C. BRAIN BASES OF BINDING IN EPISODIC MEMORY D. WHAT IS KNOWN ABOUT DEVELOPMENT OF BRAIN AREAS RELEVANT TO EPISODIC MEMORY? E. SUMMARY

IV.

MEMORY IN THE FIRST 2 YEARS

V. VI.

IMPLICIT MEMORY IN THE ABSENCE OF EXPLICIT MEMORY? ARE THERE BIOLOGICAL BASES FOR THE LIFTING OF INFANTILE AMNESIA? A. CONTEXT AND THE VPC TASK B. DELAYED NONMATCH TO SAMPLE C. PLACE LEARNING D. OTHER SPATIAL TASKS E. SUMMARY

VII.

ARE THERE BIOLOGICAL BASES FOR THE LIFTING OF CHILDHOOD AMNESIA? A. SOURCE MEMORY B. BINDING C. SUMMARY

VIII.

ALTERNATIVE CONCEPTUALIZATIONS OF THE DEVELOPMENT OF EPISODIC MEMORY A. WHAT ARE THE ROLES OF OTHER LINES OF DEVELOPMENT IN THE DEVELOPMENT OF EPISODIC MEMORY? B. QUALITATIVE VERSUS QUANTITATIVE CHANGE IN THE DEVELOPMENT OF EPISODIC MEMORY

IX.

CONCLUSION

REFERENCES 37 Advances in Child Development and Behavior R.V. Kail : Editor

Copyright © 2007 Elsevier Inc. All rights reserved.

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Nora S. Newcombe et al. You’ve made it through 365 days of sleep deprivation and diaper changes! But it’s all been worth it. It’s Baby’s First Birthday!! While your baby may appreciate it someday, know that 1-year-olds will have no memory of the big celebration—so be sure to have a camera on hand for the classic photo or video footage of your frosting-covered 1-year-old. A short, sweet celebration is recommended to accommodate baby’s nap time (http://www.chiff.com/entertain/first-birthday.htm).

This excerpt from a Web guide to planning birthday parties takes for granted that children will not remember events in their infancy—even the most festive or emotional. That first taste of fudge icing, the exciting feeling of wearing a party hat and being the center of attention, the bouncy notes of Happy Birthday sung by adoring relatives—all these experiences will be lost if not recorded on film. Why should this be true? And how can we square this lack of memory with the impressive array of data suggesting that babies are learning a great deal about their environment and that their early experiences affect their development? How could babies acquire their first words without being able to form memories, or how could they form attachment relationships to particular adults without remembering faces and voices? Clearly, there is a mystery here. The inaccessibility of early event memories in later life is sometimes called infantile amnesia and sometimes called childhood amnesia. Interest in the phenomenon began with Freud (1905/1953) but was sporadic through most of the twentieth century, although there were occasional essays (e.g., Schactel, 1947) and empirical investigations (e.g., Rubin, 1982; Waldfogel, 1948) devoted to it. However, Pillemer and White’s (1989) thoughtful review chapter jump-started modern research on the topic, and investigations have since accumulated at an accelerating rate. Several books have been devoted in whole or in part to early autobiographical memory and the problem of infantile or childhood amnesia (e.g., Bauer, 2006b; Howe, 2000; Pillemer, 1998). We are learning a great deal about key aspects of early event memory. Nevertheless, several problems have not yet been addressed adequately. The first key issue is the description of what is meant by infantile and childhood amnesia. Infantile amnesia and childhood amnesia are often considered synonymous terms, so that investigators envision a unitary phenomenon. Consequently, there is much discussion of questions such as when “it” is offset, or if “it” is real, and so forth. Actually, however, we argue that the situation is more complex. There seem to be two separable phenomena, an early 2-year period of dense amnesia, from which people remember close to nothing, and a subsequent period lasting about 3 to 5 years during which amnesia is lifting, but from which people retain some spotty and uneven memories.

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A second issue arises from the fact that our current understanding of memory development emphasizes early competence and the existence of explicit memory even in infancy (for review, see Bauer, 2006b; Chapters 7–10 in Oakes & Bauer, in press). Thus, a reading of the contemporary memory literature might persuade one that observations of infantile amnesia are somehow simply erroneous. Perhaps, properly understood, we remember as much from the first 2 years as can be expected, given the long delays involved or the likelihood that what was encoded initially does not match later conceptual frameworks used at retrieval. A slightly different but related viewpoint is the claim that any deficiencies in early memories arise from continuously developing processes, with no qualitative differences in memory as children develop (e.g., Bauer, 2006b; Courage & Howe, 2004). In this chapter, we take a different tack on this matter. Working within the paradigm of contemporary cognitive neuroscience, we argue that, although implicit memory and explicit semantic memory are present early on, there is no good evidence of early episodic (and autobiographical) memory in infancy. Indeed, this state of affairs may have functional significance, because building semantic knowledge about a new world is a primary task for infants and toddlers, and doing so efficiently may be easier when episodic aspects of acquisition events are not retained. For example, it is more important for babies to learn the word “banana” than to remember where or from whom they learned it. In this fashion, we propose a solution to the apparent paradox of excellent infant memory coupled with poor adult memory of early events—we are talking about different kinds of memory. In doing so, we also suggest an important discontinuity in memory development. A third issue revolves around the causes of early amnesia (among writers who accept its existence). Many investigators argue that the primary cause of increasing autobiographical memory is change in children’s language, cognition, and social interactions (for review, see Nelson & Fivush, 2004). We argue that such changes provide some part of an explanation of early memory development, but not a complete one. Consideration of these factors should be augmented by an examination of changes within the mnemonic system itself, at both the behavioral and the neural levels. Let us preview our hypotheses even more specifically. We argue for early functioning of implicit memory (in its various forms) as well as of semantic memory during the initial period of infantile amnesia, but with extremely limited episodic memory based on the immaturity of areas of the medial temporal lobe. Thus, we propose an analogy between infants and toddlers on the one hand and people suffering from hippocampal damage on the other and further suggest that hippocampal maturation may account for the developmental transition occurring at around 2 years (see Bachevalier, 1990; Nadel & Zola-Morgan, 1984; and Schacter & Moscovitch, 1984; for similar claims but with different

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dating of transitions). In making this argument, we present data from development in several spatial tasks known to depend on the hippocampus, exploiting the idea that the human hippocampus may subserve functions related to both the spatial domain and episodic memory, perhaps because both functions require the binding together of various cues in the environment (O’Keefe & Nadel, 1978; Rolls, Stringer, & Trappenberg; 2002). We then argue that the period of childhood amnesia may be analogous to source amnesia and that changes across this period may be linked to maturation of function in prefrontal cortex, as previously suggested by Schacter, Kagan, and Leichtman (1995). We also consider the possibility that, alternatively or in addition, hippocampal areas may continue to develop across this time period. The plan of the chapter is as follows. We begin by considering delineation of the phenomenon and the case for two distinct periods. We then proceed to discuss two important bodies of literature that form essential background for conceptualizing the development of memory: first, the question of how to define the human memory system and its components, including how we define autobiographical and episodic memory, and second, what is known about the brain bases of episodic and autobiographical memory. In the main body of the chapter, we discuss the development of episodic and autobiographical memory, beginning with whether there is evidence for episodic as well as semantic memory in the first 2 years of life. Following this discussion, we consider whether early memories can be retained in implicit form, even in the complete absence of explicit memories, as occurs with dense amnesics; whether biological factors contribute to the end of infantile amnesia; and whether biological factors contribute to the gradual lifting of childhood amnesia. We end by relating this discussion to two claims concerning autobiographical memory development: that it is primarily the product of developments in nonmnemonic domains, such as sense of self, ideas of narrative structure, recognition of the social importance of remembering, and linguistic development, and that it is quantitative in nature rather than showing qualitative transitions.

I. Differentiating Infantile and Childhood Amnesia Infantile or childhood amnesia is often treated as a unitary phenomenon, but mounting evidence suggests that it is probably complex and multiply determined (Neisser, 2004). One key distinction that may contribute to understanding our lack of early event memories is that there seem actually to be two phenomena that constitute two distinctive periods of early amnesia. The first period encompasses the first 2 years, a period from which very few if any events are consciously recalled. For this period, there may be a productive analogy to what researchers examining individuals with brain damage call dense amnesia. The second period encompasses the next 3 to 5 years, a period during which events

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are recalled at lower rates than might be expected from a normal forgetting function, may be remembered in an unusually fragmentary form, and may seem globally familiar rather than specifically recallable. For this period, there may be a productive analogy to what researchers examining individuals with brain damage call source amnesia. To keep matters straight, we refer to the first period as infantile amnesia and the second as childhood amnesia. One line of evidence favoring the delineation of these two separate periods comes from the distribution of autobiographical memories through the first decade of life, acquired from studies that ask people for large numbers of such memories using various probe techniques. For example, people may be asked to recall past events that relate to specific cue words, such as “sand,” and then asked to date the memories. Several studies have been conducted that chart the frequency of events recalled from childhood as a function of the age of the child when they occurred (Crovitz & Schiffman, 1974; Crovitz & Quina-Holland, 1976; Waldfogel, 1948; Wetzler & Sweeney, 1986). Rubin (2000) constructed an overall distribution relating age to frequency of memories, based on an assembly of about 11,000 childhood memories gathered in various studies using the probe technique and other methods. The resulting curve, shown in Figure 1, shows very few autobiographical memories predating the age of 2 years, with a rising but still small number of memories evident in the interval between turning 2 and turning 3. The number of memories increases steeply thereafter, but levels

Fig. 1. The distribution of memories as a function of age, which demonstrates the rapid increase in autobiographical memories during very early childhood and maturation of memory around 7 years of age (adapted from Rubin, 2000).

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off beginning at about the age of 5 years, with mature levels clearly evident by around 7 years, so that adults remember events from later elementary school at about the levels predictable from the time elapsed since the events. Thus, it appears that autobiographical memory over the first decade of life can be characterized as showing three different periods: in the first, there are almost no autobiographical memories; in the second, autobiographical recall is increasing rapidly; and in the third, autobiographical memory is at mature levels. Other lines of evidence favor the kind of curve delineated by Rubin and the notion of two separable periods of early amnesia followed by mature functioning. First, looking at the proposed demarcation between infantile and childhood amnesia at around 2 years, data from studies in which people have been asked about single specific events likely to be memorable, such as birth of a younger sibling or a hospitalization, reveal verified recall of some aspects of such events beginning at around the age of 2 years but extremely rare, and close to nonexistent, before (Crawley & Eacott, 1999, 2006; Eacott & Crawley, 1998, 1999; Sheingold & Tenney, 1982; Usher & Neisser, 1993; Winograd & Killinger, 1983). An alternative demarcation point might be suggested at 3 years, based on studies asking people to recall and date their earliest memory. Such dates cluster around 3 years, although they vary somewhat depending on age, gender, and culture (Fiske & Pillemer, 2006; Kihlstrom & Harackiewicz, 1982; MacDonald, Uesiliana, & Hayne, 2000; Matsumoto & Stanny, 2006; Mullen, 1994; Peterson, Grant, & Boland, 2005; Wang, 2001). It is reasonable, however, to suppose that questioning regarding the “earliest memory” is a relatively insensitive assessment of the offset of infantile amnesia, because people do not know a priori what their earliest memory is. Given the scarcity of memories from the ages of 2 and 3 years, they are quite likely to hit on a memory from when they were 3 as their earliest if they simply conduct a random search of those memories and perhaps especially if they first retrieve the most vivid. Asking for recall of known (and verifiable) events seems to be the stronger method because this is a more targeted way to investigate what if any memories from earlier time periods are available. Second, demarcating childhood amnesia and ordinary forgetting at around 5–7 years can also be supported by other kinds of findings, besides the data summarized by Rubin. For one thing, studies asking about memory of specific events such as hospitalizations show steep increases across the age range from 2 to 6 years, similar to the increases seen in Figure 1. Unfortunately, they rarely include data on events experienced at later ages, such as 10 or 12 years, to establish whether there is a leveling at adult levels during the elementary school years. One exception is work examining memory of the German invasion of Denmark in 1940 and the end of the German occupation in 1945 (Berntsen & Rubin, in press). This study found that memories of these events increased linearly up to as late an age as 8 years and remained level thereafter. However, this study is not definitive, because by 8 years memories were at ceiling levels (so development might continue even later) and, in addition, because these events, though dramatic, may have been difficult for

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children younger than 8 years to understand, and adults may have sheltered them from discussion of at least the first event (so mature memory might be seen earlier had children really known about the events when they happened). Clearly, more research along these lines, using different events, would be welcome. Another line of evidence relative to the age at which mature memory for events appears is obtained when people are asked to judge whether events in their early childhood were simply known from others’ reports or actually remembered. The median age of remembered events is around 6 years (and the median age of events simply known about from family stories is around 3 years) (Bruce, Dolan, & Phillips-Grant, 2000; Bruce et al., 2005; Multhaup, Johnson, & Tetirick, 2005).1 Overall, autobiographical memory appears to reach mature levels in the early school years, between the ages of 5 and 7.

II. Architecture of the Human Memory System The psychology of memory has a long history, dating back to Ebbinghaus’ heroic work with his own memory for consonant–vowel–consonant trigrams in the nineteenth century. A notable feature of that approach was that investigators assumed that there was a single entity called “memory,” whose laws they were aiming to discover. The advent of information processing theory led to functional distinctions, as between sensory stores, short-term memory and long-term memory (Atkinson & Shiffrin, 1968), or between memory tasks such as recognition and recall (e.g., Mandler, Pearlstone, & Koopmans, 1969; Warrington & Weiskrantz, 1970), or, in a path-breaking effort, between episodic and semantic memory (Tulving, 1972). However, toward the end of the twentieth century, the study of memory and its development was transformed by a new way of thinking about long-term memory. Understanding this approach, and how to define autobiographical memory within it, is key to analysis of the development of autobiographical memory. A. A MODERN TYPOLOGY OF LONG-TERM MEMORY The modern framework was inspired by findings that individuals with brain damage could show evidence of forming new memories, as long as one considered 1

Bruce et al. (2000) suggested that the mean of the two ages, which was 4.64 years in their study, provides an estimate of the end of childhood amnesia because at that age the amount of recallable memories exceeds the amount of events that are known from others. In fact, based on estimated ages to which memory fragments (as opposed to more extended events) are dated, Bruce et al. (2005) argue for 3 years as the age of offset of childhood amnesia. We believe, however, that these estimates fail to distinguish infantile amnesia from childhood amnesia. The earliest age at which anything can be verifiably remembered is different from the age at which memory begins to obey the laws of normal forgetting.

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that explicit, conscious, verbal access was not the essential attribute of memory. So, for example, amnesic patients can learn and retain a new motor skill (e.g., Milner, 1962), such as playing an acceptable game of golf even while forgetting what shots were made on a previous hole (Schacter, 1983). Similarly, prosopagnosic patients who do not recognize even very familiar faces can show facilitated perceptual processing of faces seen before (de Haan, Bauer, & Greve, 1992), and implicit and explicit memory are dissociated in posthypnotic amnesia (Barnier, 2002). Even normal adults showed evidence of this kind of phenomenon (Jacoby & Dallas, 1981). Findings of this sort gave rise to a distinction between declarative and procedural memory (e.g., Squire, 1986; Squire & Zola-Morgan, 1988) or, alternatively, between explicit and implicit memory (e.g., Schacter, 1987). Explicit or declarative memory refers to the ability to consciously retrieve memories based on previous experience and knowledge, whereas implicit or procedural memory refers to evidence that past experience influences perceptual processing or other kinds of responses without conscious awareness.2 There has been some criticism of this kind of distinction from proponents of a unitary memory store, who suggest that the difference might amount to little more than one between stronger and weaker memory traces (e.g., McBride & Dosher, 1997; Ratcliff & McKoon, 1996; Shiffrin & Steyvers, 1997) or might confound other relevant distinctions (Roediger & Blaxton, 1987). However, data regarding the neural bases of memory have tended to support the idea of a fundamental dichotomy, which is now widely if not universally accepted. The dichotomy is not, however, the end of classification. There are also important distinctions within the realms of explicit (or declarative) and implicit (or nondeclarative or procedural) memory. Figure 2 displays a modern typology. With regard to the first realm, the fundamental contrast is that between semantic and episodic memory proposed originally by Tulving (1972), although refined subsequently (Tulving, 1983, 1986, 2002; also see Schacter, 1987; Schacter & Tulving, 1994). With regard to the second realm, there seem to be several different kinds of memory that are not explicit, but that are also quite different from each other. Implicit memory is divided into procedural skill (the kind of motor memory we mentioned above, such as memory for a golf swing), associative memory (including various kinds of classical conditioning and perhaps with further subdivisions), nonassociative learning (such as habituation), and priming (which includes changes in perceptual skill such as increased rapidity of identification or identification under degraded conditions). 2

However, see Mandler (2004) for arguments that the implicit–explicit distinction is not exactly the same as the procedural–declarative distinction.

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Memory

Declarative

Nondeclarative

Semantic

Episodic

Facts

Events

Skill

Priming

Dispositional

Nonassociative

Motor Perceptual Cognitive

Perceptual Semantic

Simple Classical Conditioning

Habituation Sensitization

Shifts in Judgement and Preferences

Operant Conditioning

Adaptation Level

Fig. 2. A contemporary depiction of human memory illustrating the distinctions within declarative and nondeclarative systems.

B. WHAT IS AUTOBIOGRAPHICAL MEMORY? How does autobiographical memory fit into this scheme? A good deal of discussion has addressed the question of defining autobiographical memory (e.g., Brewer, 1986). One simple way to think about the matter is to suggest that semantic and episodic memory can each concern the self (or not). That is, we can define a 2 ⫻ 2 table such as the one shown as Table I, with autobiographical memory occupying the bottom cell on the right (i.e., episodic memory of a selfrelated kind). Autobiographical memory is thus distinct from autobiographical knowledge (I know that I was born in Toronto, and this is a self-related piece of semantic knowledge, but I have no memory of the event). Self-related episodic memory is also distinct from impersonal episodic memories such as those studied in many traditional memory experiments (the memory of being in a free recall experiment and seeing “tree” on a word list is only trivially part of my autobiography). One advantage of this categorization is that it suggests that much of what we know about the development of episodic memory from research on classic episodic memory tasks that are not self-related (e.g., free recall) may also apply to autobiographical memory. Because there is a large volume of such research (e.g., see review by Schneider & Bjorklund, 1998), considering its relevance for autobiographical memory development is worthwhile. For example, perhaps some of the phenomena of the period of childhood amnesia can be explained by young children having strategy deficits of various kinds. That is, older children who are asked about their third grade classroom might first start by thinking of their teacher or friends. Younger children are less likely to guide their memory

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Episodic

Impersonal

Paris is the capital of France That’s a picture of Al Gore

Self-related

I was born in Toronto That’s a picture of my mother

“Tree” was on the free recall list A picture of that face was in this experiment My picnic was last Sunday That’s a picture of the guy I met at Joe’s party

searches in such a way and thus may appear not to remember, when in reality, they are not performing in a way that promotes remembering. In addition, they may be more prone to actually forgetting, due to the lack of memory review. An elaboration on this typology suggests that episodic memory is actually composed of interdependent facts that could individually be considered to be semantic memories. Thus, for example, I know that I own a green flowered skirt, I know that I went to a certain concert, and I know that my friend Lily went to the same concert. Individually, these could be considered semantic memories, two of which are self-related. But when they are put together, so that I know that I wore the skirt when I went to the concert with Lily (and especially when joined with other facts such as what we ate first, how we got to the concert, where it was, what the music sounded like, and so forth), we have an episodic memory of the autobiographical kind. The literature has termed this process of putting together aspects of a situation feature binding (e.g., Mather et al., 2006). However, two important unsettled issues are associated with this way of defining autobiographical memory. First, Tulving (1993; Wheeler, Stuss, & Tulving, 1997) has described episodic memory as mental time travel, using the term autonoetic recall to refer to the capacity to be aware of past, present, and future experience. In doing so, he emphasizes the vividness and particularity of episodic memory in general and autobiographical memory in particular. Many people agree that these qualities are distinctive characteristics of what they mean subjectively by autobiographical memory. In contrast, a great deal of evidence dating back to Bartlett indicates that memory is reconstructive, and many researchers have emphasized that autobiographical memory is no exception. In a position close to the opposite of Tulving’s, Conway and Pleydell-Pearce (2000) have argued that what we call autobiographical memory is constructed in working memory given the current state of the self. The construction uses autobiographical knowledge in long-term memory and is somewhat grounded by it, but that knowledge is also in turn influenced by the construction generated. An intermediate position is taken by Johnson and her collaborators, whose source monitoring framework for thinking about autobiographical memory also attributes

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importance to inference processes and yet retains the construct of self-related episodic memory as a real entity rather than one undergoing potentially infinite constructive modification (Johnson, Hashtroudi, & Lindsay, 1993). A second issue concerns the role of emotion and the self. An autobiographical memory seems to many writers to be more than simply an episodic memory in which one is a participant. My memory of going to the concert with Lily also includes components that are unique to the fact that I was a participant, such as what I thought and what I felt, and the memories are spatially and temporally constrained by my sensorimotor experience; that is, by real-world facts about where I went at what time. Factors such as self-reflection and personal temporality seem to be essential aspects of autobiographical memory (Klein et al., 2004). In summary, autobiographical memory can usefully be considered as episodic memory that relates to the self and that, as such, is likely to be more emotional and more personally meaningful than episodic memories that lack such relevance. As with all memories, inference is used in constructing and evaluating recall and recognition attempts, and hence memory is far from veridical. Nevertheless, autobiographical memory may have a phenomenological quality of “mental time travel” to the extent that it includes a great deal of interlinked information. Autobiographical memory is a uniquely important kind of episodic memory because of its relevance to human cognitive and emotional life: people treasure their personal memories and work to retain them by making scrapbooks, taking photos, sharing them at family gatherings, and so on.

III. Brain Bases of Human Memory One of the reasons for adopting the typology of long-term memory shown in Figure 2 is that researchers have documented the varying areas of the brain that have specific roles in each of the postulated types of memory. Specifying such brain bases gives us a purchase for thinking about the memory system and its development that is lacking in purely behavioral approaches. A. ROLE OF THE HIPPOCAMPUS IN EPISODIC AND SEMANTIC MEMORY One manner of distinguishing brain areas that is controversial, in a way that is important for this chapter, is the idea of a common base for episodic and semantic memory. This conceptualization has been widely endorsed, with the view being that, for any kind of explicit memory, the hippocampus is important early in memory encoding and during a consolidation process during which it acts as a pointer to information stored neocortically, with ultimate dependence only on neocortex (e.g., Alvarez & Squire, 1994; McClelland, McNaughton, & O’Reilly,

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1995). An alternative is that semantic memory depends on temporal lobe cortex surrounding the hippocampus, whereas episodic memory depends either on the hippocampus proper (Mishkin et al., 1997) or on the hippocampus plus certain other parts of the hippocampal complex (Hayes et al., 2004) and, furthermore, that the hippocampus is always involved in retrieval of episodic memories, not just during a period of consolidation (Nadel et al., 2003). The evidence for thinking that episodic and semantic memory are supported by somewhat different brain systems and that the hippocampus is important to episodic memory on a continuing basis comes from three sources: reinvestigations of classic cases of adults with hippocampal lesions such as H.M., studies of developmental amnesics (i.e., children who suffered hippocampal damage early in life), and imaging studies of normal adults. 1. Reconsidering Amnesia With respect to dense amnesia of the kind caused by large bilateral hippocampal lesions and that afflicts well-known patients such as H.M., the prevailing wisdom had been that there was an inability to form new explicit memories, either semantic or episodic, along with well-preserved semantic and episodic memory for material learned before the operation or accident. However, two subsequent findings cast doubt on this generalization. First, amnesics, including H.M., can apparently acquire at least some new semantic information. For example, in the context of his hobby of solving crossword puzzles, H.M. is helped by semantic clues referring to postoperative facts and names (Skotko et al., 2004). H.M. also appears to have acquired postoperative semantic information about the names and accomplishments of individuals who became famous after his operation occurred in 1953, such as John Glenn (O’Kane, Kensinger, & Corkin, 2004). Second, preoperative autobiographical memory is more impaired than previously imagined, for H.M. and for two other patients, W.R. and K.C. (Rosenbaum et al., 2005; Steinvorth, Levine, & Corkin, 2005). (Preoperative semantic knowledge is in fact well preserved, as has always been believed.) The difficulties with preoperative episodic memories and the ability to acquire postoperative semantic memories suggest a continuing and central role for hippocampus in episodic and autobiographical memory and a less important role for hippocampus in semantic memory. 2. Developmental Amnesia Cases of developmental amnesia support the hypothesis that hippocampus is not central to semantic memory encoding and retention. Children exposed to hypoxia sometimes develop bilateral hippocampal abnormality, with reductions in hippocampal volume ranging from 43 to 71% (de Haan et al., 2006). Their temporal lobe regions are usually well within normal range, suggesting that damage is restricted to the hippocampus. When studied in later childhood and

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adulthood, they show severe episodic memory impairments but apparently wellpreserved ability to form semantic memories. Delayed recall tests prove extremely difficult, while scores on tests of immediate memory and recognition are within the normal range compared to healthy controls (Baddeley, VarghaKhadem, & Mishkin, 2001; Gadian et al., 2000; Vargha-Khadem, Gadian, & Mishkin, 2001; Vargha-Khadem et al., 1997). Additionally, these children have significantly impaired spatial memory (King et al., 2004) and are not well oriented in the temporal elements of events, such as the date and time. Two of three reported developmental amnesia cases (Vargha-Khadem et al., 1997) accumulated semantic memory of factual knowledge after hippocampal damage (sustained at birth). This supports the account that for episodic functioning the hippocampus is primarily associated with recall and binding contextual information of events, whereas the surrounding parahippocampal structures may provide more support for semantic memory based on recognition and familiarity. As pointed out by de Haan et al. (2006), a very interesting aspect of these cases is that, even when damage is sustained in infancy, impairments do not become evident until children reach school age. One possible reason for this pattern is that semantic memory normally develops first, and hence the difficulties of children exposed to hypoxia are not noted by observers until the age at which normal children begin to exhibit strong episodic memory skills. Interestingly, the timing of 6 years or so for the age at which deficits are first apparent fits well with the offset age for childhood amnesia that we described previously. 3. Imaging of Normal Adults Imaging studies conducted with normally functioning adults also support an important role for the hippocampus in autobiographical recall. Researchers have found hippocampal activation when people recall information about contextualized and interlinked objects, people, locations, and times, such as who gave you an object when and where (Burgess et al., 2001; Hayes et al., 2004). Hippocampal activation appears independent of the age of the autobiographical memory, thus casting further doubt on the notion of a consolidation process after which the hippocampus is not involved in recall (Addis et al., 2004; Gilboa et al., 2004; Maguire & Frith, 2003a, 2003b; Rekkas & Constable, 2005; Ryan et al., 2001). Notably, qualities of the recollection such as detail and emotionality are correlated with variations in hippocampal activation (Addis et al., 2004). Some aspects of these findings have yet to be worked out: hippocampal activation that is independent of the age of the memory may be restricted to the left hippocampus (Maguire & Frith, 2003b), or remote and recent memories may activate different parts of the hippocampus (Gilboa et al., 2004). But the continued involvement of the hippocampus in autobiographical recall seems clear.

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B. ROLE OF THE FRONTAL LOBES IN EPISODIC AND SEMANTIC MEMORY People with damage to frontal cortex have memory problems, although they are not nearly so marked as the afflictions of people with damage to medial– temporal areas. However, frontal patients do show large and significant decrements in recall, as well as small but still significant decrements in recognition (for a review, see Wheeler, Stuss, & Tulving, 1995). One particularly interesting phenomenon shown by frontal patients has been termed source amnesia. People with source amnesia can learn new information, but they have great difficulty later in knowing when, where, and from whom they learned it (Schacter, Harbluk, & McLachlan, 1984). Such problems suggest not only forgetting of sources, narrowly construed, but also difficulty with episodic memory, which requires the interlinking of who–when–where information with semantic facts. Studies using fMRI or other techniques to image brain functioning of normal adults suggest that left prefrontal cortex may be particularly important for detailed episodic remembering, for autobiographical memory, and for source judgments (e.g., Conway et al., 2003; Ranganath, Johnson, & D’Esposito, 2000; Raye et al., 2000; but see Thaiss & Petrides, 2003), although localization to the left is not a universal finding (Greenberg et al., 2005; Hayes et al., 2004; Vandekerckhove et al., 2005). The nature of the role of prefrontal cortex in episodic and source memory is not yet clear. Consistent with the role of prefrontal cortex in executive function more generally, strategic retrieval and evaluation processes may be the domain of this brain area, coupled with coactivation of memories in areas concerned more specifically with memory such as the hippocampus (Cabeza et al., 2004; Greenberg et al., 2005; Vandekerckhove et al., 2005). Additionally, prefrontal cortex may be involved during autobiographical memory retrieval due to the relevance of some areas in prefrontal cortex for selfreferential processing (Cabeza et al., 2004; Keenan et al., 2000). An important aspect of recalling life events is differentiating what really happened from what was imagined or heard from a third party. Imagined or recounted events appear to be differentiated from experienced ones by more perceptually relevant areas being active during remembering of the latter (Cabeza et al., 2004; Conway et al., 2003; Slotnick & Schacter, 2004). Thus, prefrontal cortex may be involved in reality monitoring through a role in appraisals of these activation patterns. C. BRAIN BASES OF BINDING IN EPISODIC MEMORY We have mentioned that the ability to link together different aspects of experience is central to the formation of an event memory. Such binding processes have sometimes been studied in situations in which people are asked to remember intraitem associations, such as the color as well as the shape of an object

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(e.g., Wheeler & Treisman, 2002), as well as in situations in which people are asked to remember interitem associations such as the location of objects (e.g., objects are shown against backgrounds, and people are probed on their memory for the unique relation of the object and the background) or word relations (e.g., Naveh-Benjamin, 2000). Interitem associations may be especially relevant to event memory, because they serve to create the what–where–when structure of autobiographical narrative, although the study of intraitem associations is also interesting. Studies of contextual binding suggest the importance of the hippocampus for the binding process and for the decrements in binding observed in the elderly (Chee et al., 2006; Goh et al., 2004; Mitchell et al., 2000a). Thus, we should consider whether hippocampal change, extending through 5 years of age or even later, might be linked to a growing ability to form interitem associations that eventually leads to an end of the period of childhood amnesia.

D. WHAT IS KNOWN ABOUT DEVELOPMENT OF BRAIN AREAS RELEVANT TO EPISODIC MEMORY? We have identified numerous brain areas important to episodic memory, including most notably the hippocampus and prefrontal cortex. Thus, it is natural to ask what is known about development of these areas. Could immaturity in one or both of them contribute to infantile or childhood amnesia? Unfortunately, the current literature does not provide a great deal of guidance. For prefrontal cortex, the problem is that development is known to extend across a very long developmental span, with initial synaptic proliferation followed by a pruning process and other associated changes that extend into late adolescence (Giedd et al., 1999; Huttenlocher & Dabholkar, 1997; Sowell et al., 2001). Thus, almost any developmental change could be plausibly linked to changes in prefrontal cortex, given that we do not know in a detailed way the level of maturation in different areas needed to support specific functions. For the hippocampus, the problem is that we have very little direct information. Many researchers have read the sparse literature as suggesting that maturation of this area occurs very early in life (e.g., Nelson, 1995), although other sources describe changes that extend over the first 5 years or even beyond (Alvarado & Bachevalier, 2000; Gogtay et al., 2006; Seress, 2001; Utsunomiya et al., 1999). Given this situation, we present data gathered inferentially from behavioral techniques. That is, if a particular task is known to recruit a certain brain area, such as hippocampus, based on data from nonhuman animals, imaging of normal adults, or work with patients with brain damage, then the development of success on the task may provide an indirect assessment of maturation of the brain area. This strategy entails many assumptions. When data from nonhuman

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animals are used, we assume parallels across species. This matter is debated sometimes but there is solid evidence for evolutionary continuity in function, at least for the hippocampus (Kesner & Hopkins, 2006). When tasks that are nonmnemonic in nature are used, we assume that brain areas that support more than one function can be assessed using either one. In particular, the hippocampus seems particularly central both to spatial and to episodic memory, a linkage that may be far from accidental (as suggested originally by O’Keefe & Nadel, 1978, and discussed since by many authors, e.g., Rolls et al., 2002; Whishaw & Wallace, 2003). Spatial memory and navigation require the contextual linkage of a variety of relevant cues to location, so that a structure evolved to allow for successful spatial behavior might be particularly well suited also to encoding contextualized events. E. SUMMARY Episodic memory, in general, and autobiographical memory, in particular, depend on both prefrontal cortex (which may be especially involved in effortful retrieval and strategic memory decisions) and on hippocampus (which may be especially involved in storage of memory traces themselves and the binding of various traces to form an interlinked context-specific memory). In addition, various other brain areas may be involved, most notably when emotion is retrieved or when specific sensory detail is accessed. Relatively little of a specific nature is known about the development of the hippocampus and prefrontal cortex, although frontal development is a lengthy process and hippocampal development probably extends through at least 5 years. Notably, brain areas involved in semantic memory may be different from those involved in episodic memory, so that the two forms of explicit memory may be more distinct than is often recognized.

IV. Memory in the First 2 Years Scientists still debate the presence of explicit memory in the first 6 months of life. During this early period, the available techniques for assessing memory are visual-paired comparison, which measures how much infants look at novel as opposed to familiar stimuli, and the conjugate reinforcement paradigm, which examines infants’ rates of kicking when they see mobiles that have formerly been controllable in that way. Both of these paradigms are sometimes argued to reflect implicit rather than explicit memory (Bauer, DeBoer, & Lukowski, in press, on conjugate reinforcement; Snyder, in press, on visual-paired comparison), although some vigorously advocate the view that they tap explicit memory (Rose, Feldman, & Jankowski, in press, on the visual-paired comparison paradigm, and Rovee-Collier, 1997, on conjugate reinforcement). However, there is

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consensus that explicit memory is clearly evident by 6 months of age from experiments using deferred imitation of action sequences, a technique that passes the “amnesia test,” that is, impaired performance in both adults with hippocampal damage (McDonough et al., 1995) and cases of developmental amnesia (Adlam et al., 2005). Deferred imitation of a series of experimenter-modeled actions can first be demonstrated at 6 months, albeit in simple forms involving short sequences, brief delays, or repeated retrievals (Barr, Dowden, & Hayne, 1996; Barr, Rovee-Collier, & Campanella, 2005). Memory as assessed by deferred imitation strengthens in various ways through the first 2 years, becoming capable of more complex encodings that last over longer retention intervals and that require less specific cues for retrieval (Hayne, Boniface, & Barr, 2000; Hayne, MacDonald, & Barr, 1997). These findings bring us to a conundrum. By at least the second year of life, action sequences are well retained over periods of several months (e.g., Bauer, Hertsgaard, & Dow, 1994; Bauer, Hertsgaard, & Wewerka, 1995), and everyone seems now to agree that such memory is explicit in nature. Given that fact, how is it possible that later on, autobiographical memories will be close to nonexistent? This question might have several answers. One possibility is that explicit memory, even in the second year of life, is still insufficiently robust to allow for the formation of memories that will survive retention periods of decades. However, the data on retention over lengthy periods of time reduce the plausibility of this argument. Another possibility is that early explicit memory may be semantic in nature rather than episodic. Remembering the sequences shown in deferred imitation experiments, such as three actions required to make a rattle, may yield a memory regarding how to make a rattle that is not linked to where one learned it, from whom, with what materials, and so on. Indeed, data on deferred imitation and retention of action sequences show that children often do generalize over such dimensions (Bauer & Dow, 1994; Lechuga, Marcos-Ruiz, & Bauer, 2001). Although they may perform better with the original materials than with analogous ones, it is not clear that an advantage for the original materials indicates specific episodic recall. It could also derive from the original objects being better retrieval cues, as when bread is a better cue for butter than milk is. Clearly, generalization of what is learned would be adaptive: it is far more important for children to learn facts and skills than to know the circumstances in which they were acquired. Unfortunately, there is no direct evidence on the episodic versus semantic nature of memory in the first 2 years of life. The lack of linguistic skills in this period always poses a challenge to delineating such matters. However, researchers have addressed the issue using nonverbal means, and there have been claims of startling episodic skills in nonhuman animals who seem to remember specific details about past experiences (with scrub jays—Clayton & Dickinson, 1998, 1999; Clayton, Yu, & Dickinson, 2001, 2003; with pigeons—Zentall et al.,

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2001; with rats—Babb & Crystal, 2006; Kart-Teke et al., 2006). For example, taking advantage of the natural caching behavior of scrub jays, Clayton and Dickinson (1998) observed that the birds would return to search for previously stored perishable items only after short delays, switching to nonperishable food after a long delay, indicating an episodic-like memory for where and when certain foods were stored and where to locate them following a variable delay. Although these results from nonhuman animals are susceptible to a semantic memory interpretation (repeated reinforced trials may produce rule learning rather than reliance on memory of specific events), that possibility too could perhaps be excluded in further research. The first step is to adapt such techniques for use with young children, as pioneered by Hayne (in press) with preschool children. The hypothesis that early explicit memory is semantic but not episodic is strikingly supported by the studies of children suffering from developmental amnesia, who can acquire a normal store of semantic knowledge and who certainly learn to speak, but who have very deficient episodic memory abilities. There are, however, no definitive demonstrations in normal children either of the hypothesis that early memory is not episodic or of the alternative that it is. Nevertheless, the supposition does solve the issue of how one could have early explicit memory and yet little if any autobiographical recall. Mandler (2004, pp. 239–240) summarized the situation in a similar way: None of the experimental data [on infant memory] provides any evidence for spatiotemporal dating of these memories. Indeed, it seems somewhat unlikely that when an observed event comes to mind at a later time the infant is also aware of when or where it happened. Spatiotemporal dating is not required for recall…By age 2, verbal recall protocols suggest some awareness of when and where events being recalled took place…but this issue has not been systematically studied…We also do not know whether these early recall memories are autobiographical.

If we adopt the supposition that early explicit memory is semantic but not episodic as a working hypothesis, what then are the remaining puzzles about early autobiographical memory? We see four key questions: (1) Can memories be retained in implicit form, even in the complete absence of explicit memories, as occurs with dense amnesics such as H.M.? (2) Is there a role for hippocampal development, and perhaps prefrontal development, in the end of infantile amnesia? (3) What are the roles of later hippocampal development and/or frontal development in the gradual lifting of childhood amnesia and the development of source memory? (4) How does this discussion relate to other conceptualizations of early autobiographical memory, such as the claim that memory development is quantitative rather than showing qualitative transitions or claims that development of autobiographical memory is primarily the product of developments in other domains, such as sense of self, ideas of narrative structure, recognition of the social importance of remembering, and linguistic development?

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V. Implicit Memory in the Absence of Explicit Memory? Fairly soon after studies of implicit memory in normal adults began appearing, there were demonstrations that preschool children showed good implicit memory also. The research mainly involved perceptual priming, in both visual and auditory modalities, and the conclusion emerged that these abilities did not develop but were present in mature form early on (Carroll, Byrne, & Kirsner, 1985; Church & Fisher, 1998; Greenbaum & Graf, 1989; Mitchell, 1993; Naito, 1990). Some findings challenge this generalization. Priming that depends on conceptual relations sometimes shows age-related change (e.g., Mecklenbrauker, Hupbach, & Wippich, 2003; Murphy, McKone, & Slee, 2003; Perruchet, Frazier, & Lautrey, 1995), but this seems unsurprising in light of the fact that concepts are changing and knowledge is accumulating (Lloyd & Newcombe, in press). More broadly, in terms of the overall picture in implicit memory, findings that implicit sequence learning shows age-related change (Thomas & Nelson, 2001; Thomas et al., 2004) suggest that different forms of implicit memory may have different developmental functions. Priming may be present early, but other forms of implicit memory appear to develop. As we have seen, patients suffering from amnesia, or other cognitive difficulties such as prosopagnosia, often show evidence of implicit memory even when explicit memory is impaired. Is the same phenomenon observable developmentally? That is, do children show at least some forms of implicit memory, most especially perceptual priming, in cases in which explicit memory is lacking? Several studies have addressed this issue in the context of a naturalistic situation, namely memory shown by elementary school children for faces of preschool classmates they had not seen since preschool (Newcombe & Fox, 1994; Lie & Newcombe, 1999). Other work has examined the question in the context of a more controlled experiment, assessing memory for novel pictures that were shown to children for durations and at times that were experimenter-determined (Drummey & Newcombe, 1995). In all studies, we studied explicit memory by asking for recognition judgments, but methods for assessing implicit memory varied. The first study of memory for faces of preschool classmates used galvanic skin response to assess implicit memory (Newcombe & Fox, 1994), whereas the other used a behavioral measure involving judgments of whether faces viewed from different perspectives were the same or different (Lie & Newcombe, 1999). The technique was based on previous work with normal adults and adults suffering from prosopagnosia, adapted for use with children by Newcombe and Lie (1995). Implicit memory for novel pictures was examined using a technique commonly used in the developmental and adult priming literature, namely perceptual identification of blurry pictures gradually brought into focus, where previously seen pictures are typically recognized at higher degrees of fuzziness (Drummey & Newcombe, 1995).

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All three studies revealed evidence that implicit memory can be evident in children even when explicit memory is lacking. Newcombe and Fox (1994) identified one group of children who had fairly good recognition memory for their classmates and another group who showed no evidence of recognition. The striking finding regarding implicit memory was that galvanic skin responses (GSR) were not only reliably above chance overall, but equivalent for the two groups. That is, the group of children who could not recognize pictures of their former classmates did show implicit responsivity to their pictures at levels equal to those who did recognize them (see Figure 3). Lie and Newcombe (1999) found higher levels of recognition than Newcombe and Fox did and hence were not able to identify a group of children who showed no evidence of explicit memory. They did, however, compare performance on the implicit task for pictures of classmates who were and were not correctly recognized and found equivalent levels of accuracy on the implicit task for classmates in the two categories. Drummey and Newcombe (1995) studied children 3 months after the initial showing of a picture book, as well as immediately. After 3 months, 3-year-old children showed no evidence of picture recognition, but they did show reliable perceptual priming. In addition, comparison to older children and adults showed that recognition memory showed marked age-related increases, as would be expected of an explicit memory measure, but perceptual priming was developmentally invariant.3 Taken together, these data suggest that implicit memory can indeed be preserved when explicit memory is lacking. This statement should not be taken to

Fig. 3. Equivalent implicit memory performance (measured by galvanic skin responses) despite differences in explicit (recognition memory) performance (from Drummey & Newcombe, 1995). 3

Adult priming was at surprisingly low levels, a finding for which we have no real explanation.

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imply, however, that implicit memory does not decay. GSR responses in the Newcombe and Fox (1994) data were better than chance at statistically reliable levels, but accuracy was low relative to what would be expected from prior studies of prosopagnosics. In addition, perceptual priming declined over the 3-month interval in the Drummey and Newcombe (1995) study. Similarly, in Lie and Newcombe (1999), accuracy on the implicit measure declined significantly across that 3-year period. One question that this group of studies cannot answer is whether implicit memory based on experiences occurs in the first 2 years of life, the period of infantile amnesia. Although some children in the preschool classmate studies entered group care as infants, we could not identify any large subset of situations in which two infants were in the same group early on, but were separated subsequently as opposed to continuing to attend the same childcare center. The only research that may address survival of implicit memory comes from followup work on children who participated in research on auditory localization at about 6 months of age (Myers, Clifton, & Clarkson, 1987; Perris, Myers, & Clifton, 1990). Two years later, they were more likely than control children who had not been in the situation before to retain the old action sequences and be able to grasp the object that was making a sound. With rare exceptions, they did not show evidence of explicitly recalling having been in the situation before. However, the status of retention of action sequences as a measure of implicit versus a form of explicit memory is not secure. Action sequences are exactly what deferred imitation tasks assess, and those tasks have been convincingly shown to be explicit in nature. Nevertheless, the follow-up studies on auditory localization also report evidence of differential reactions to the situation itself, such as greater comfort being in the dark, that do seem likely to be implicit in nature. Clearly, more work on implicit memory in the first 2 years of life is needed. First, we need to determine definitively if implicit memory exists at all. There is actually very little evidence regarding how early we can see evidence of perceptual priming, with or without concomitant explicit memory. To our knowledge, there are no studies of priming in children younger than 3 years using techniques analogous to those used with older children and adults. Although priming as defined within the conjugate reinforcement paradigm is evident in very young infants (Rovee-Collier, 1997) and infants and adults show analogous repetition priming as assessed by event-related potentials (Webb & Nelson, 2001), the evidence is too scarce to conclude that perceptual priming is present in infancy. Second, we need to address whether, if priming exists, it survives (or other kinds of implicit memory last) in cases in which explicit memory formed by infants fades. The Myers et al. (1987) and Perris et al. (1990) studies are suggestive, but not definitive.

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VI. Are There Biological Bases for the Lifting of Infantile Amnesia? So far, we have proposed that early explicit memory is primarily or entirely semantic in nature—although the existence of early episodic memory needs to be more directly addressed. We have also suggested that implicit memory may be available from the period of infantile and childhood amnesia—although there is not nearly as much direct evidence concerning the period of infantile amnesia as one would like. In this section, we consider the proposition that the apparent lack of episodic memories in the first 2 years of life reflects the relative immaturity of the hippocampus. The relevant data come from several nonmemory tasks: a variant of the visual-paired-comparison task (VPC), the delayed-nonmatch-to-sample (DNMS) task, and several spatial tasks including place learning. A. CONTEXT AND THE VPC TASK As we have mentioned, success in VPC is evident very early in life and is widely assumed to show explicit rather than implicit memory (although see Snyder, in press, for doubts). However, in a variant of the procedure, success is not observed until between 12 and 18 months of age (Robinson & Pascalis, 2004). In this situation, a picture of an object is presented to an infant on a solid-colored background. Then, pictures of a novel object and the old object are shown in a paired comparison test, in which background color either remains constant or changes to another color. When the color context is changed, babies do not show memory for the objects until between 12 and 18 months. This fact is intriguing, given evidence that the same difficulty is shown in monkeys with hippocampal lesions (Pascalis & Bachevalier, 1999) and in an amnesic patient with bilateral hippocampal damage (Pascalis et al., 2000). The transition between 12 and 18 months is earlier than the offset of infantile amnesia at 2 years, but the finding is broadly consistent with the idea of developments in hippocampally based memory functions that are later than often postulated (e.g., Nelson, 1995). However, further studies are needed to understand the bases of lack of novelty preference with changing backgrounds. Later in development, relating objects to their backgrounds proves challenging (Sluzenski, Newcombe, & Kovacs, 2006), but at this earlier age, it seems as if the objects and their backgrounds are too tightly bound together, so that change in the color of a background creates a new stimulus. B. DELAYED NONMATCH TO SAMPLE In the DNMS task, a novel object is presented, removed, and then presented again, together with a new novel object. The correct response is to select the object that differs from the one previously presented. Success on DNMS is

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known to depend on medial–temporal lobe structures (e.g., Malkova et al., 2001). One would imagine that success on this task would appear early in life, because the required response is almost identical to the response required in the VPC—the baby simply has to reach for a novel object rather than look at a picture of a novel object. Nonetheless, success on the classic version of DNMS is not seen until 21 months of age (Diamond, 1990; Overman et al., 1992). Success is, however, seen earlier when the reward for a correct choice is directly attached to the selected object using Velcro on the base, rather than located in a well revealed by moving the selected object (Diamond et al., 1999). Further work has shown that the key element crucial for early success is the physical connectedness of the object and the reward—spatial and temporal proximity are not essential (Diamond, Lee, & Hayden, 2003). From these data, the argument has been made that the hippocampus matures early, supporting memory for objects, and that what infants and toddlers need to acquire is the ability to make the connection between the response and the reward when they are not physically connected, which may depend on another brain area: the periarcuate region of the prefrontal cortex (Diamond, 2006). Unfortunately, we do not know as much as we would like about the brain bases of performance on the modified DNMS task. The classic DNMS task may require the hippocampus not so much for the memory demands of the task, which are quite slight, but to establish the relation of the object to the reward when they are not physically connected. In contrast, the modified version of the task does not require the child to make the connection between the object and the reward because they are physically connected. Thus, the modified DNMS task might require less involvement of the hippocampus than the original task. Some evidence for this idea comes from the fact that animals with hippocampal damage are known to approach discrimination-learning problems in a fundamentally abnormal way (O’Keefe & Nadel, 1978). Instead of initially learning the association between a particular reward and a specific location or item, these animals associate rewards with a particular response. Thus, patients with hippocampal damage or monkeys with hippocampal ablations might succeed at the modified DNMS task, but this hypothesis has not so far been tested. It may be that the late age at transition to success on the classic DNMS task (21 months) remains diagnostic of hippocampal maturity.

C. PLACE LEARNING Place learning is the ability to locate a position using information about its distance and direction from distal landmarks. Research on the development of place learning has been conducted both in rats and in human children. Beginning with the research on rats, studies have delineated a detailed description of the timing

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and sequence of acquisition, mostly using the Morris water maze (Morris, 1984). In this task, a rat is placed in a circular pool of murky water and must swim to a platform hidden just under the surface of the water to escape the water, which functions as an aversive stimulus. Because nothing in the pool itself can guide their search, rats find the platform only if they use landmarks outside of the pool, thus demonstrating place learning. Preweanling rats are able to solve the water maze at 20–26 days (Rudy & Paylor, 1988; Rudy, Sadler-Morris, & Albert, 1987; Schenk, 1985), or at a slightly younger age when pools are smaller (Carman & Mactutus, 2001) or when body temperatures are kept close to normal so that the physical act of swimming is less physiologically challenging (Brown & Whishaw, 2000). After 26 days, rats continue to improve in their ability to place learn (Brown & Kraemer, 1997; Schenk, 1985). Maturation of the hippocampus is likely to be one of the principal mechanisms underlying development of the place learning system. We have long known that the hippocampal formation is required for success in the water maze when there are no coincident landmarks (Morris, 1984). The hippocampus of infant rats shows extensive development in the first week after birth and continues to develop for at least a few weeks after that. The cell density in the dentate gyrus of the hippocampus reaches adult levels at about 25 days and the hippocampus shows metabolic activity from around 30 days (Schenk, 1985). The developmental milestones seen with the behavioral place-learning tasks correspond roughly to the developmental course of the hippocampus, providing suggestive evidence that the development of the hippocampus is involved with the development of place learning (Nadel & Zola-Morgan, 1984; Schenk & Morris, 1985). A similar situation may obtain for humans. Human place learning is also supported by the hippocampus, based on studies involving both brain-injured and normal human adults (Bohbot et al., 1998; Holdstock et al., 2000; Iaria et al., 2003; Maguire et al., 1998; Maguire, Frackowiak, & Frith, 1996, 1997), including a study using single-cell recording techniques, which allow for more precision in understanding the nature of the neural structures supporting task performance (Ekstrom et al., 2003). In children, place learning is first seen around 21 months of age (Newcombe et al., 1998). Newcombe et al. (1998) examined the development of the use of distal landmarks located at the edges of a room that contained a centrally located sandbox. Children ages 16–36 months observed a toy being hidden in the rectangular sandbox, were moved to the opposite side, and then searched for the toy. Half the children performed this search with visible landmarks in the room and half without visible landmarks (because a circular white curtain surrounded the sandbox). Children 22 months and older performed better when the landmarks were visible, but younger children did not. In other words, children younger than 22 months did not seem to use the distance from surrounding objects to locate objects after movement; that is, they did not exhibit what has been called place learning. These results are

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consistent with earlier work (Bushnell et al., 1995; DeLoache & Brown, 1983; Mangan et al., 1994). As with rats, earlier roots of place learning may be evident in simpler situations, albeit in environments that do not require the use of distance and direction from several landmarks considered together (Clearfield, 2004; Lew, Bremner, & Lefkovitch, 2000; Lew et al., 2004). In addition, place learning is not complete when it is first observed at 21 months. It continues to develop well into the school years, with children showing increasing precision in their use of increasingly more distal landmarks in increasingly complex settings (Laurance et al., 2003; Leplow et al., 2003; Overman et al., 1996; see review by Learmonth & Newcombe, in press). Nevertheless, first emergence of recognizable place learning at 21 months is a strong clue that this may be a time of important hippocampal change with implications for mnemonic functioning. D. OTHER SPATIAL TASKS Changes in performance on several other spatial tasks also support a developmental shift toward increased hippocampal functioning at the end of the second year of life. Prior work on children’s memory for spatial location of objects using the sandbox paradigm (Huttenlocher, Newcombe, & Sandberg, 1994; Newcombe et al., 1998) had examined memory for only a single object, hidden for less than a minute. To be useful, however, spatial location memory needs to allow for representing multiple locations, to allow for the learning of spatial relations among objects, and to support recall after a substantial filled delay. Sluzenski, Newcombe, and Satlow (2004b) tested children from 18 to 42 months on three more complex sandbox search tasks: recall of two locations rather than just one, learning a spatial relation between two objects, and retaining the location of a single object over a filled delay. Results indicated a marked transition in the ability to perform at nonchance levels on all three tasks that occurred between 18 and 24 months, with moderate age-related improvement thereafter. Similar data have been reported by another research group: children between 18 and 24 months show a sharp increase in the ability to remember multiple locations over delays of 20 min and 24 h by finding hidden objects among an array of three hiding spaces (Russell & Thompson, 2003).4 Each of these tasks is known to have hippocampal bases. Monkeys with hippocampal resections show impairments in remembering two locations (but not one) even after only a very brief delay, suggesting that the ability to represent

4

Although Moore and Meltzoff (2004) found accurate performance by 14-month-olds after a 24-h delay, their hiding situation involved very distinctive locations and a very highly marked hiding procedure, and they did not examine age-related change.

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multiple objects requires intact hippocampal structures (Angeli, Murray, & Mishkin, 1993; Parkinson, Murray, & Mishkin, 1988). Lesions to hippocampal structures impair performance on conditional spatial discrimination tasks similar to the relational task of Sluzenski et al. (2004b) both in animals (Kimble, 1963; Marston, Everitt, & Robbins, 1993) and in humans (Daum et al., 1991; Myers et al., 2000). Hippocampal lesions lead to impairment in the memory for a single location with delays as brief as 10–20 s when egocentric responding cannot be used to solve the task (Bohbot et al., 1998; Long & Kesner, 1998). E. SUMMARY The existing evidence, although still sparse, suggests the possibility of a general transition in hippocampal functioning toward the end of infancy, in which a capability emerges for durable and complex memory that involves contextualized coding. In the VPC work, abstracting the object away from its background may be an essential prerequisite for distinguishing episodic elements that should be encoded separately (for some purposes) and yet bound together (for others). In the DNMS work, relating an action to a separated consequence could be considered an aspect of contextualized memory, perhaps requiring hippocampus, although an alternative is that such linkage depends on a region of prefrontal cortex. Perhaps the strongest support for an important watershed in behaviors that are hippocampally based comes from the place-learning research, with support from three other lines of spatial memory development (recall of two locations, learning a spatial relation, and retaining the location of a single object over a filled delay). Nevertheless, we must recognize that all of this work is highly inferential and future research is needed along many lines, including work that more finely distinguishes among different areas of the hippocampus and the hippocampal complex (Nemanic, Alvarado, & Bachevalier, 2004). In addition, it would be interesting to gather data with infants and young children on other tasks with strongly established hippocampal substrates, such as certain kinds of classical eyeblink conditioning (Green & Woodruff-Pak, 2000).

VII. Are There Biological Bases for the Lifting of Childhood Amnesia? During the period between 2 and 6 years, children show clear evidence of episodic memory and recall of autobiographical events. For example, they can report on distinctive events such as class field trips several weeks, and even years, after the events occurred (e.g., Hudson & Fivush, 1991), although such reports are typically heavily scaffolded by adults. In addition, as older children

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and adults, they will have access to memories of some of these events, although these memories will be fewer than one might predict (Rubin, 2000). Thus, this period seems much less mysterious than the first 2 years of life, when there is little evidence of episodic memory and from which events are rarely if ever recallable in adult life. Nevertheless, there are questions about episodic functioning in this period. In this section, we review evidence for discontinuities in this period, and their possible biological bases, in two areas: source memory and binding. These abilities are centrally important functions that are necessary for achieving episodic recall that interlinks various aspects of an event to create a memory of a specific experience taking place at a certain time and place and enriched with perceptual and emotional detail. As might be expected given this description and the facts about offset of childhood amnesia already discussed, they are not robustly present in children until the age of 6 years or so. A. SOURCE MEMORY As already mentioned, patients with frontal lobe lesions appear to suffer from source amnesia (Janowsky, Shimamura, & Squire, 1989; Schacter et al., 1984; Shimamura & Squire, 1987). When taught new facts (which they retain quite well), they are far more likely than controls to make erroneous source attributions. These errors go beyond simply confusing plausible sources such as two experimenters, each of whom taught certain facts. Instead, frontal patients also make extraexperimental errors, in which they claim to have read the facts in TV Guide, known them from childhood, or so on. Similar problems with source errors have been found in elderly individuals, who often suffer from subtle difficulties with frontal function (Craik et al., 1990; McIntyre & Craik, 1987). These data suggest that extraexperimental errors in source memory paradigms may serve as a marker for frontal functioning. Such errors are directly relevant to the growth of episodic memory, because access to details of who was present at events, as well as where and when events happened and perceptual detail regarding them, are exactly what we mean by episodic and autobiographical memory. The ability to encode, retain, and recall source is not readily apparent at the age of 3 years. The developmental course of the appearance of this ability is charted in various paradigms. Some studies of source memory in children, conducted as part of research on theory of mind, have shown marked improvement between 3 and 4 years (Gopnik & Graf, 1988; Perner & Ruffman, 1995; Taylor, Esbensen, & Bennett, 1994; Wimmer, Hogrefe, & Perner, 1988). Investigators in the theoryof-mind tradition have typically asked children how they know something (e.g., How do you know that the child will search for the smarties in the pencil box?), and the jump in performance at 4 years is typical of the age-related changes found

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in other theory-of-mind tasks, such as questions about the appearance versus the real nature of objects that look like something different from what they are (e.g., a sponge that looks like a rock). If source memory were truly mature by 4 years, however, changes in source memory would fit poorly with the slower lifting of childhood amnesia, which takes a good deal longer. These studies may, however, have found relatively early success at source tasks because they offered children a forced choice among plausible alternatives and, thus, did not allow for the possibility of extraexperimental errors. In addition, they used very short delays. To assess developmental change in extraexperimental errors, Drummey and Newcombe (2002) devised a child-appropriate analogue to the fact-teaching paradigm used by Schacter et al. (1984). Either an experimenter or a puppet taught 4-, 6-, and 8-year-old children novel (but true) facts such as that the Nile is the longest river in the world. One week later, when children remembered a fact, they were asked how they knew this information. In these circumstances, 4-year-olds made an astonishing number of extraexperimental errors (59%), whereas 6- and 8-year-olds committed such errors at relatively low levels and did not differ from each other (13 and 19%, respectively; see Figure 4). Because extraexperimental errors are signatures of frontal lobe deficits, the results suggest a dramatic change between the ages of 4 and 6 years in the ability of that cortical area to support mnemonic functioning. Additionally, Drummey and Newcombe (2002) looked at correlations between source memory and behavioral measures of frontal functioning (category generation, a modified Wisconsin card sort, and a modified Stroop task). Higher scores on the card-sort task predicted fewer extraexperimental errors

60 4-year Olds 6-year Olds 8-year Olds

Percent(%)

50 40 30 20 10 0 Correct Source

Extra Errors

Intra Errors

Fig. 4. Source attributions (correct, extraexperimental, and intraexperimental) after a 1-week delay for new facts learned by 4-, 6-, and 8-year-old children (from Drummy & Newcombe, 2002).

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among a group of 4-year-olds not showing ceiling levels of such errors, even after controlling for a measure of general intelligence. However, the other two putative frontal measures did not show such correlations. The correlational approach is simply not a very powerful tool for the examination of biological bases of memory. Modern statistical analyses such as structural equation modeling or hierarchical linear modeling may provide a better approach for understanding the relationships between test and task performance. Another way to examine source memory is suggested by the source monitoring framework developed by Johnson et al. (1993). People must often distinguish between whether they really did something or only imagined doing it, a judgment that has been termed reality monitoring. The data on source memory in preschool children are mixed. On the one hand, by 4 years of age, performance in source-monitoring tasks is already at above chance levels in some situations (Lindsay, Johnson, & Kwon, 1991; Welch-Ross, 1995). On the other hand, with more difficult tasks, such as distinguishing between internally generated stimuli (thoughts versus actions) or making distinctions after substantial delays, developmental improvement continues into the school years (Parker, 1995; Sussman, 2001). Sluzenski, Newcombe, and Ottinger (2004a) noted that much of the previous work on reality monitoring has involved isolated actions or short sequences rather than extended naturalistic events. This fact limits its implications for the development of autobiographical memory, as does the fact that reality monitoring has often been assessed after brief intervals. Accordingly, Sluzenski et al. (2004a) studied 4-, 6-, and 8-year-olds who were engaged in four events, such as making a greeting card or unpacking a picnic basket. Two events were enacted using real objects, while the other two events were imagined, guided by a taped description. When reality-monitoring judgments were elicited, especially after a week’s delay, 4-year-olds had more trouble than older children distinguishing between real and imagined events. This difficulty appeared despite the fact that independent assessment of the characteristics of their memories (i.e., with free recall, cued recall, and recognition) showed that they had the inferential bases for a distinction (e.g., they retained more perceptual detail regarding really experienced events). Younger children’s problems with reality monitoring seemed to derive from two sources: first, in some cases, their memories were at levels low enough that they provided unreliable guides for judgment, and second, strategically, they may not have realized that differences in the characteristics of their memories allow them to decide whether something really happened. The experiments by Sluzenski et al. (2004a) are intriguing for consideration of autobiographical memory, in part because after delays of a week, children often erred in reality monitoring by saying that an experienced effect was imagined rather than vice versa. In studies with short delays, the opposite error is usually

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more frequent. Believing that something real was imagined seems, over the really long run of years, to be likely to result in a paucity of autobiographical memories. This pattern of data may represent an instance of attributing memory characteristics poorly. That is, perhaps children failed to appreciate the effect of delay on the quality of their memories. When events happened recently, resulting in relatively strong memory traces, they were assumed to be experienced, whereas, once the memory had weakened, children assumed the event must have been imagined. By adulthood, one is better able to account for differences in memory strength (e.g., Hoffman, 1997). In Sluzenski et al.’s (2004a) experiments, the only assessments of linkage to frontal function were again correlational, but that strategy did achieve some positive results. Looking at the data across experiments revealed several noteworthy relations between episodic memory for events and fluency of category generation as a measure of frontal functioning, even after controlling for age and scaled vocabulary scores. The clearest relations were between category fluency and free recall of the events; free recall may be a purer measure of episodic memory than cued recall or recognition, in which associative strategies and responses to general familiarity likely come into play. In summary, there is evidence that 4-year-olds show important deficiencies, relative to school-aged children, in the ability to avoid extraexperimental errors on source tasks and in the ability to distinguish between events they really experienced and those they only imagined. These abilities are relevant to the problem of childhood amnesia from a functional point of view, in that a memory will not seem convincingly autobiographical if its context and, most important, its veridicality, are not retained. The findings also buttress the argument that changes are related to biological changes in prefrontal functioning, most strikingly because extraexperimental errors are a hallmark of adults with damage to that area, but also, more weakly, based on some correlational evidence.

B. BINDING In many ways, the essence of episodic memory is the binding together of relations among co-occurring stimuli (Johnson & Chalfonte, 1994; Schacter, Norman, & Koutstaal, 1998). It is possible to remember an aspect of a situation (e.g., “I have met Elfrida Oliphant”) without remembering Elfrida’s face, where or when you met her, what she said to you, and so on. These different kinds of information need to be interrelated, probably independently; put another way, an event is not a holistic entity but instead the assemblage of a net of pair-wise associations (Trinkler et al., 2006). In fact, memory for isolated aspects of what were originally experienced as events is essentially what we mean by semantic memory: knowing Elfrida is a fact about oneself rather than an autobiographical

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memory. Given this analysis, it is surprising that relatively little attention has been paid in developmental research to the development of binding, especially since a good deal of work with the elderly suggests the interdependence of binding deficits with declines in source monitoring and episodic memory (Castel & Craik, 2003; Chalfonte & Johnson, 1996; Chee et al., 2006; Li, Naveh-Benjamin, & Lindenberger, 2005; Mitchell et al., 2000a; Mitchell et al., 2000b). Sluzenski et al. (2006) aimed to create a task to study the early development of binding that would be motivating for young children and easy for them to understand. In particular, they sought to develop engaging stimuli and settled on a task in which pictures of animals were shown against complex backgrounds, as shown in Figure 5. These backgrounds were not the animals’ natural habitats, to avoid confounding age with knowledge of animals and where they usually live. Instructions drew children’s attention to the backgrounds as well as the animal and ensured that they understood the kinds of recognition judgments we asked them to make. When tested in the same session as that in which acquisition occurred, recognition of animals alone and of backgrounds alone did not differ between 4- and 6-year-olds or between 6-year-olds and adults. Such equivalence is necessary to evaluating the possibility of age differences in binding, because if either kind of information is not encoded well, clearly binding would not be expected. Against this baseline of age-equivalent memory for component information, it was

Fig. 5. Example of the complex stimuli used to test memory binding in young children (from Sluzenski et al., 2006).

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interesting that 6-year-olds were more likely than 4-year-olds to bind that information together, remembering not just that they saw a lion, or not just that they saw a certain street scene, but that the lion was on that street. By contrast, 6-year-olds and adults did not differ. In a second experiment designed to assess developmental improvements in binding (Kovacs, Hansell, & Newcombe, 2005), the stimuli were simpler and more similar to those used in prior studies with elderly populations. Participants looked at line drawings of simple objects such as umbrellas done in colored ink. They later decided whether they had seen a black-and-white umbrella (item memory alone), a certain shade of green before (color memory alone), and a green umbrella (assessment of binding). Item and color memory were both accurate but not ceiling levels across age, indicating that all age groups had access to the required featural information. Nevertheless, the same developmental pattern in binding emerged as that seen by Sluzenski et al. (2006) differences between 4- and 6-year-olds but no differences between 6-year-olds and adults. Thus, it appears that between the ages of 4 and 6 years, children’s performance in learning relations among different aspects of a stimulus improves significantly. C. SUMMARY In this section, we have reviewed evidence of marked changes between the ages of 4 and 6 years in the ability to retain bound information that supports episodic recall and that allows for the accurate reporting or reconstruction of source information, regarding both who said something and also whether an event really happened. These changes are interdependent, as was most clearly seen in the Sluzenski et al. (2004a) study, in which the ability to judge whether something really happened depended in part on levels of memory for the component aspects of the episode from which a judgment could be made, but younger children also lacked the ability to use the characteristics of their memory to make judgments. The overall thrust of this work so far is simply to support the proposition that age changes in episodic and autobiographical memory during the preschool years are intertwined with these more basic memory processes in terms of overlapping developmental curves and (sometimes) correlational relations (although those are methodologically more difficult to assess). In addition, evidence tentatively links these behavioral changes to development in functioning of prefrontal cortex, most strikingly in the extraexperimental error data of Drummey and Newcombe (1995). However, hippocampal functioning may also be relevant to development of episodic memory in preschool children, especially in the case of feature binding, because binding is known to depend on hippocampus.

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VIII. Alternative Conceptualizations of the Development of Episodic Memory In this chapter, we have advanced the case for distinctive periods in the development of autobiographical recall and for distinctive biological reasons for the phenomena of infantile and childhood amnesia. The research basis for these assertions in the work of developmental psychologists is relatively sparse, but the hypotheses gain in weight from consideration of related work in adult memory, memory and aging, comparative cognition, and the biological substrates of memory processes. Nevertheless, although the ideas are plausible, we recognize that this conceptualization differs from many other contemporary views of memory development, which tend to emphasize early competence, developmental continuity, and social reasons for change (e.g., Bauer, 2006a, 2006b; Howe & Courage, 1993, 1997; Nelson & Fivush, 2004). In this section, we concentrate on ways in which our framework differs from other approaches to early memory development. Our overall message is that many (although not all) of the differences among approaches are more apparent than real and that the various traditions of inquiry are actually providing complementary information. A. WHAT ARE THE ROLES OF OTHER LINES OF DEVELOPMENT IN THE DEVELOPMENT OF EPISODIC MEMORY? Young children’s recall of events is related to their understanding of how to structure a narrative, to their developing understanding of social situations and acquisition of scripts for events, and to the cultural demands placed on them for telling stories about their experience (see Nelson & Fivush, 2004, for review). This general style of theorizing encompasses many specific lines of inquiry including, for example, studies showing that parental interaction shapes children’s memories through focusing attention on the past and scaffolding accounts of past events (e.g., Haden et al., 2001; Mullen, 1994; Reese, Haden, & Fivush, 1993) and that discussion about past events is related to event memory (e.g., McGuigan & Salmon, 2004) and further related to the development of self concept (“an autobiographical self,” e.g., Bird & Reese, 2006). Other studies show fascinating cultural variation in the development of autobiographical memory (e.g., Wang, 2006; Wang et al., 2006). For example, Chinese children remember less about past events than their Euro-American peers, a difference that turns out to be mediated by their lower levels of knowledge about emotional situations. In addition to the substantial amount of attention that has been devoted to social interaction and cultural variation in autobiographical memory development, other research has focused on contributions of cognitive and language development to personal event memory. In terms of cognitive development,

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Howe and Courage (1993, 1997) have linked the end of infantile amnesia at around 2 years to the acquisition of a concept of self. In addition, research has shown that children are unlikely to retain memories of events that they poorly understood at the time they occurred, such as a fire alarm evacuation at a preschool (Pillemer, Picariello, & Pruett, 1994). In terms of language development, research has shown that autobiographical memories are more easily retrieved when queried in the language used at the time of acquisition (e.g., Marian & Neisser, 2000), which has supported a correlated idea that perhaps language is simply too poorly developed in early childhood to allow the encoding and rehearsal necessary for accurate explicit memory. In addition, children apparently cannot easily “translate” their memories from a preverbal format to a linguistic format as language development proceeds (Simcock & Hayne, 2002). These explanations of failures to retain autobiographical memories all center on the idea that improvements in socioemotional understanding, cognitive abilities, or language will lead to improvements in memory performance. All of these factors are likely important in the mix of changes resulting in the emergence of mature levels of autobiographical recall. The question is whether any one change, or even the entire set of proposed changes, can alone account for the phenomena. We think social, cognitive, and language changes external to the memory system itself have difficulty accounting for some aspects of memory development. For example, consider what we know about face recognition. As we have seen, recognition memory for faces of children known during preschool survives only at fragile levels in later childhood (Newcombe & Fox, 1994; Lie & Newcombe, 1999). However, language development seems quite unsuited to accounting for this phenomenon, because faces are not linguistically encoded (Hancock, Bruce, & Burton, 2000). Nor can it be said that young children are not interested in faces or fail to understand their significance, because we know that faces are vitally important even to newborns (Morton & Johnson, 1991). It is likely that infants’ and preschoolers’ attention to faces and motivation to remember them are at ceiling levels. Thus, without considering the development of memory systems themselves, it is hard to explain why we have such difficulty remembering the faces of people with whom we interacted extensively in the first 5 years of life. Furthermore, all of the factors described here are likely to contribute individually and in interaction with other factors. One example of this phenomenon comes from another study of source monitoring done in our lab (Kovacs & Newcombe, 2006). Adults’ source judgments are more accurate when they focus on speakers’ emotions rather than focusing on their own emotions (Johnson, Nolde, & DeLeonardis, 1996), perhaps because thinking about the speaker encourages processing of the perceptual characteristics of that person, as well as binding of that perceptual information to the content of what is being said. But a great deal of developmental work suggests that younger children are less likely

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to spontaneously adopt the perspective of another person than older children, so we wondered to what extent the age-related differences in source memory that we had observed in Sluzenski et al. (2004a) were due to changes in encoding focus. In three experiments, we found that, when 4- and 5-year-olds heard an audiotape (or saw a videotape) of two similar (or dissimilar) speakers, 5-yearolds were more likely to show better source memory when asked to adopt another person’s focus, although 4-year-olds did show a benefit under supportive conditions in which the sources were made very distinctive, the task instructions were thoroughly explained, and the information was presented in several formats. Overall, the data suggest that the benefit for source memory of focusing on another person develops over the preschool years with easy tasks showing sensitivity before more difficult source judgments. Of course, in life outside the laboratory, we are not prompted to think about the emotions and thoughts of others. Examination of the development of spontaneous focus on others might well show substantial contributions of parental interaction and culture to this kind of thought, which in turn supports source encoding, which in turn supports autobiographical recall. Multidirectional webs of causation should not exclude the analysis of the brain substrates of memory functions. Experience is often vital in stimulating brain development (Greenough, Black, & Wallace, 1987; Shonkoff & Phillips, 2000). Thus, hippocampal and prefrontal “maturation” is likely a misnomer if maturation is taken to imply a passive, autonomous process that goes on at a standard developmental pace irrespective of what children are doing and being asked to do. Instead, demands to remember events and support in evoking recall may well lead to accelerated development of the frontal–hippocampal circuitry that enables this function. Thus, social factors such as the push from some adults for children to be able to recount events in their day may act on memory by driving brain development, rather than simply working at a functional level.

B. QUALITATIVE VERSUS QUANTITATIVE CHANGE IN THE DEVELOPMENT OF EPISODIC MEMORY Debates about whether developmental change is qualitative or quantitative in nature are long-standing, typically highlighted in introductory textbooks as one of three or four key questions about human development. However, this dichotomy is more apparent than real. Smith and Thelen (1993) talk about how the “view from above” makes qualitative differences seem salient, while the “view from below” emphasizes ongoing, fine-grained, quantitative change. Elman et al. (1996) discuss in detail how quantitative change at one level of analysis can lead to emergent qualitative change, a familiar example being quantitative changes in temperature that span freezing or boiling points. Thus, claims

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that early episodic memory is fundamentally similar to mature memory, differing only in quantitative aspects of encoding efficiency or storage duration, seem to miss the discontinuity at another level of analysis, namely in whether events will later be retrievable at all (for infantile amnesia) or at adult levels (for childhood amnesia) (see Courage & Howe, 2004, for recent discussion of this position). That is, if encoding is insufficient to allow for retrieval of an event in later life, a change that is quantitative at one level of analysis has created an effect (inability to remember the first 2 years of life) that is qualitative at another level of analysis. A separable issue is whether any hypothesized qualitative change occurs abruptly or has a single cause. Such changes have been claimed in the literature on autobiographical memory development: For example, Howe and Courage (1993, 1997) propose that self-recognition brings the period of infantile amnesia to a close. The answer to the abruptness question is clearly that change is almost always gradual; in this chapter, even when we have reviewed some transitions that are abrupt within a single study, as in the data of Newcombe et al. (1998) on place learning or Drummey and Newcombe’s (2002) findings on extraexperimental source errors, we see also that, with suitable task changes, there are earlier precursors of transition and later refinements to a competence, often taking years. This fact makes analysis of congruencies in developmental curves challenging, although not impossible. The answer to the second question was previewed previously in our discussion of multiple causation (see also Howe, Courage, & Edison, 2003). Various factors come together in complex ways to create change and analysis of causation is challenging given the likelihood of feedback loops. To return to the hypothesis about self-recognition, emerging episodic memory may well support cognitive recognition of the self, as well as the opposite. In addition, both may depend on common biological substrates in prefrontal cortex (Keenan et al., 2000), and (lest we think we have reached bedrock by invoking biology) environmental press may in part create change in the nervous system.

IX. Conclusion People are often fascinated by memories of their earliest years, believing that they may hold the key to personal insights and opportunities for emotional growth. Nevertheless, the available evidence indicates that such memories are virtually nonexistent from the first 2 years of life and, although increasing over the next 4 or so years, are very often patchy and fog-covered until the beginnings of elementary school. This evidence sits oddly with data on the strength of memory in infancy and early childhood, leading to much excitement about a focused search for explanations of the mysteries involved in the contrast. The accumulating data

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suggest that explanations will be multifactorial rather than unitary. In this chapter, we have endeavored to make the case that an important aspect of the explanation involves research that makes full use of current distinctions regarding the architecture of the human memory system and its brain bases and that uses an array of techniques including not only developmental work but also research with braindamaged patients, nonhuman animals, and human adults studied both behaviorally and with imaging techniques. We have also argued that there are urgent unanswered questions, concerning topics such as whether memory in the first 2 years is primarily semantic. Given the pace of current progress, we are optimistic that answers to these questions, and perhaps even resolution to the mystery of early amnesia, are within our grasp. REFERENCES Addis, D. R., Moscovitch, M., Crawley, A. P., & McAndrews, M. P. (2004). Recollective qualities modulate hippocampal activation during autobiographical memory retrieval. Hippocampus, 14, 752–762. Adlam, A. R., Vargha-Khadem, F., Mishkin, M., & de Haan, M. (2005). Deferred imitation of action sequences in developmental amnesia. Journal of Cognitive Neuroscience, 17, 240–248. Alvarado, M. C., & Bachevalier, J. (2000). Revisiting the maturation of medial temporal lobe memory functions in primates. Learning and Memory, 7, 244–256. Alvarez, P., & Squire, L. R. (1994). Memory consolidation and the medial temporal lobe: A simple network model. Proceedings of the National Academy of Sciences, USA, 91, 7041–7045. Angeli, S. J., Murray, E. A., & Mishkin, M. (1993). Hippocampectomized monkeys can remember one place but not two. Neuropsychologia. Special Issue: The Neuropsychology of Animal Memory, 31, 1021–1030. Atkinson, R. C. & Shiffrin, R. M (1968). Human memory: A proposed system and its control process. In K. W. Spence & J. T Spence (Eds.), The psychology of learning and Motivation. New York, NY: Oxford Press. Babb, S. J., & Crystal, J. D. (2006). Episodic-like memory in the rat. Current Biology, 16, 1317–1321. Bachevalier, J. (1990). Ontogenetic development of habit and memory formation in primates. Annals of the New York Academy of Sciences, 608, 457–484. Baddeley, A., Vargha-Khadem, F., & Mishkin, M. (2001). Preserved recognition in a case of developmental amnesia: Implications for the acquisition of semantic memory? Journal of Cognitive Neuroscience, 13, 357–369. Barnier, A. J. (2002). Posthypnotic amnesia for autobiographical episodes: A laboratory model of functional amnesia? Psychological Science, 13, 232–237. Barr, R., Dowden, A., & Hayne, H. (1996). Developmental changes in deferred imitation by 6- to 24-month-old infants. Infant Behavior & Development, 19, 159–170. Barr, R., Rovee-Collier, C., & Campanella, J. (2005). Retrieval protracts deferred imitation by 6-month-olds. Infancy, 7, 263–283. Bauer, P. J. (2006a). Constructing a past in infancy: A neuro-developmental account. Trends in Cognitive Sciences, 10, 175–181. Bauer, P. J. (2006b). Remembering the times of our lives: Memory in infancy and beyond. Mahwah, NJ: Lawrence Erlbaum. Bauer, P. J., DeBoer, T., & Lukowski, A. F. (in press). In the language of multiple memory stystems, defining and describing developments in long-term explicit memory. In L.M. Oakes & P. J. Bauer

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ADVANCES IN THE FORMULATION OF EMOTIONAL SECURITY THEORY: AN ETHOLOGICALLY BASED PERSPECTIVE

Patrick T. Daviesa and Melissa L. Sturge-Appleb a

DEPARTMENT OF CLINICAL AND SOCIAL SCIENCES IN PSYCHOLOGY, UNIVERSITY OF ROCHESTER, ROCHESTER, NY 14627, USA b MT. HOPE FAMILY CENTER, UNIVERSITY OF ROCHESTER, ROCHESTER, NY 14627, USA

I.

OVERVIEW OF THE PRINCIPLES, PROCESSES, AND PATHWAYS IN EMOTIONAL SECURITY THEORY A. DELINEATING THE FUNCTIONALIST GOAL IN EMOTIONAL SECURITY THEORY B. DELINEATING THE FUNCTIONALIST CONTEXTS IN EMOTIONAL SECURITY THEORY C. LIMITATIONS OF PRIOR TRANSLATIONS OF THE FUNCTIONALIST PERSPECTIVE IN EMOTIONAL SECURITY THEORY

II.

DISTINCTIONS BETWEEN SECURITY IN THE INTERPARENTAL AND PARENT–CHILD SUBSYSTEMS A. THE ROLE OF ETHOLOGY IN ADVANCING THEORY ON THE RELATION BETWEEN TYPES OF SECURITY B. ETHOLOGICAL ROOTS OF DIFFERENCES BETWEEN THE TYPES OF SECURITY C. ETHOLOGICAL ROOTS OF SIMILARITIES BETWEEN THE TYPES OF SECURITY D. TOWARD A PATTERN-BASED APPROACH TO EMOTIONAL SECURITY IN THE INTERPARENTAL RELATIONSHIP

III.

FAMILY ORIGINS AND CORRELATES OF EMOTIONAL SECURITY A. THE NATURE OF THE INTERPLAY BETWEEN INTERPARENTAL CONFLICT AND CHILDREN’S REACTIVITY TO CONFLICT B. SELECTIVITY IN THE SENSITIZATION PROCESS: STIMULUS CHARACTERISTICS OF INTERPARENTAL CONFLICT C. DOMAINS OF CHILD REACTIVITY IN THE FACE OF INTERPARENTAL CONFLICT D. FAMILY ROOTS OF INDIVIDUAL DIFFERENCES IN PATTERNS OF SECURITY

IV.

EMOTIONAL INSECURITY AND CHILDREN’S DEVELOPMENTAL TRAJECTORIES A. GENERAL MECHANISMS OF EFFECT B. SPECIFICITY IN THE SEQUELAE OF PATTERNS OF SECURITY

V.

CONCLUSION

ACKNOWLEDGMENT REFERENCES

87 Advances in Child Development and Behavior R.V. Kail : Editor

Copyright © 2007 Elsevier Inc. All rights reserved.

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Although witnessing conflict between parents is a normal part of family life for children, interparental conflict is a significant public health concern by virtue of its prevalence and significant threat to children’s mental health. Reflecting the prevalence of dissolution in interparental relationships, statistical projections reveal that 50–60% of children born in the 1990s will live in single-parent homes at some period in their lives (Hetherington et al., 1998). Likewise, rates of discord and violence are relatively high among parents who remain together. Between 20 and 40% of parents who remain together report significant, clinical levels of distress in their marriage (Cummings & Davies, 1994). Exposure to these high levels of discord and conflict increases children’s risk for a wide array of psychological problems including internalizing symptoms (e.g., depression, anxiety), externalizing problems (e.g., aggression, conduct problems), social impairments (e.g., poor peer relations), and academic difficulties (e.g., Dunn & Davies, 2001; Erel & Burman, 1995; Grych & Fincham, 2001). Interparental conflict has been shown to account for 4–20% of the variation in children’s individual differences in psychological problems (Grych & Fincham, 1990) and the magnitude of risk conferred by interparental conflict is nearly twice the size of the risk associated with divorce (Grych & Fincham, 2001). Consistent with the high social importance attached to understanding the nature of risk faced by children from high-conflict homes, emotional security theory was developed by Davies and Cummings (1994) to advance an understanding of precisely how, when, and why interparental discord is associated with individual differences in children’s trajectories of mental health. At the heart of our theory is the premise that interparental conflict poses a risk to children’s adjustment by directly undermining their emotional security in the interparental relationship and compromising parent–child attachment processes through its association with parenting disturbances. Despite some initial progress in further articulating the conceptual foundation, assumptions, and predictions of emotional security theory since its inception (e.g., Cummings & Davies, 1996), theoretical advances in emotional security have become markedly slow since the start of the twenty-first century. Accordingly, the overarching aim of this chapter is to advance the main elements of emotional security theory and address the implications of these modifications for clarifying the nature of process relations among family dynamics, children’s coping and adaptation in the family, and their social and emotional development. Toward advancing and refining the theory in the present paper, we specifically explore the potential utility of integrating ethological theory as a basis for the propositions outlined in emotional security theory. Previous theoretical expositions of emotional security theory downplayed the explanatory value of evolutionary mechanisms in advancing an understanding of children’s adaptation to interparental discord (e.g., Cummings & Davies, 1996; Davies & Cummings, 1998). Echoing a caution in developmental psychopathology (Cicchetti, 1990), rejecting

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the potentially informative nature of concepts and tools from other disciplines in theory formulation runs a considerable risk of undermining advances in knowledge. Therefore, the purpose of this chapter is to revisit the promise of ethology in articulating the substance, roots, and sequelae of security goal systems in the family. As the first foray into addressing the role of ethology in emotional security theory, it is important to note at the outset that our speculative account of the advantages of a synthesis will require further elaboration and revision. As a way of familiarizing the reader with our theory, we first provide an overview of some of the main principles of emotional security theory and hypothesized pathways among children’s exposure to forms of family discord, their emotional security in different family systems, and their psychological adjustment. Figure 1, which is used as an organizing framework, is designed to assist in this task by depicting an overview of some of the key family factors, processes, and pathways in emotional security theory. Against this backdrop, we address the broad conceptual limitations of the original formulation of emotional security theory and the potential value of integrating ethological and evolutionary concepts into emotional security theory. For the remainder of the chapter, we then address how infusing an ethological approach with emotional security theory informs the different components of the model, including (1) conceptual similarities and distinctions between security in the interparental and parent–child relationships, (2) relations among family processes and children’s emotional insecurity in the interparental relationship, and (3) the implications of emotional security for children’s trajectories of psychological adjustment.

Broader Family Characteristics 1) Parenting Difficulties 2) Family Level Processes 3) Child Attributes

4a

4b

4a

4b

Child Emotional Insecurity in the Family Interparental Discord 1) Hostility 2) Disengagement 3) Poor Resolution

Interparental Insecurity 2

1

3

Child Developmental Trajectories of Adjustment

Parent-Child Insecurity

Fig. 1. A conceptual model of the primary hypothesized pathways accounting for the risk posed by interparental conflict and child maladjustment within the emotional security theory.

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I. Overview of the Principles, Processes, and Pathways in Emotional Security Theory Although research and clinical accounts repeatedly underscored the emotionladen family processes accompanying interparental conflict, emotional mechanisms did not assume center stage in any of the conceptual models of interparental discord formulated in the twentieth century (e.g., Emery, 1982; Grych & Fincham, 1990); emotional security theory was designed to address this gap. Emotional security theory is rooted in the functionalist perspective on emotion and, consequently, accepts the functionalist definition of emotion as: “The attempt by the person to establish, maintain, change, or terminate the relation between the person and the environment on matters of significance to the person” (Campos, 1994, p.1). However, this account does little to advance an understanding of children’s adaptation in contexts of interparental functioning without further articulation of two components of the definition. First, the broad definition does not precisely identify the “matters of significance” to the children. Stated in different terminology, it fails to specify the goals that are important to children. Second, adopting such an expansive definition of emotion does not, in itself, provide a vehicle for delineating the specific sets of relations “between the person and the environment” that are relevant to emotional development. Therefore, any theoretical application of the functionalist perspective requires further explication of the relevant contexts and goals in the lives of individuals. A. DELINEATING THE FUNCTIONALIST GOAL IN EMOTIONAL SECURITY THEORY Approaching the task of identifying goals, emotional security theory proposes that emotional security is a primary goal in the lives of children. Consistent with the main tenets of attachment theory, emotional security theory is a developmental theory that posits that: (1) emotional security plays a mediational role in the impact of parent–child attachment relationships on children’s normal development and developmental psychopathology (e.g., Ainsworth et al., 1978; Blatz, 1966; Bowlby, 1973; Cummings & Cicchetti, 1990) and (2) the implications of children’s felt-security in the attachment relationship extend beyond the proximal context of the parent–child relationship to affect adaptive functioning in larger family and social contexts (e.g., Bretherton, Ridgeway, & Cassidy, 1990). However, emotional security theory is different from attachment theory in its emphasis on the contexts relevant to children’s emotional security. Thus, the original contribution of emotional security theory lies in its view that it is too limiting to consider children’s emotional security as solely derived from the quality of the attachment relationship. This shift in conceptual emphasis results

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in the fundamental proposition that emotional security is a primary human goal that regulates and is regulated by children’s actions and reactions across multiple family relationships. As such, children may experience emotional security in distinct ways across different family systems such as the interparental and parent–child subsystems. Pathway 1 in Figure 1 reflects the emotional security theory assumption that children’s emotional security is derived from two different goal-directed systems of security in the family. Accordingly, preserving a sense of security in the interparental relationship is proposed to be distinct in its operation and substance from preserving a sense of security in the parent–child system despite some overlap and mutual influence among systems.

B. DELINEATING THE FUNCTIONALIST CONTEXTS IN EMOTIONAL SECURITY THEORY Given the different contexts within which the security systems in the interparental and parent–child subsystems operate, individual differences in the different types of insecurity are presumed to result from distinct experiential histories within these different contexts (Cummings & Davies, 1999; Davies & Cummings, 1994). Thus, illustrating the direct pathway component of emotional security theory, Pathway 2 posits that histories of exposure to destructive interparental conflict, characterized by hostility, disengagement, and poor resolution, directly undermine children’s security in the interparental relationship. The distinctive nature of this pathway is reflected in the hypothesis that associations between interparental discord and interparental insecurity will remain robust even after taking into account broader family characteristics such as parenting difficulties (e.g., parental unresponsiveness, rejection) (i.e., Pathway 4a). Supporting this premise, children exposed to high levels of discord between parents have compelling bases for being concerned about their safety and security, as conflicts in these homes are at elevated risk to increase tension in the family, proliferate to undermine the parent–child relations, escalate into domestic violence, and signify problems in the stability and structure of the family as a whole. In advancing to the next step of outlining how children’s concerns about security are manifested in their short- and long-term functioning, emotional security theory draws again from the functionalist perspective and its balanced focus on articulating both the subsequent benefits and the costs of emotions for human development. Underlying this broader emphasis is the view that emotions play a role as monitoring and guidance systems in the appraisal of events and motivation of behavior in relation to goal systems. This assumption is specifically instantiated in emotional security theory through the conceptualization of emotional security as a goal-corrected system. Within this system, emotional security is a goal that regulates or governs the expression of behaviors, emotions, thoughts,

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and physiological responses. Although emotional security theory postulates that concerns about security in the interparental relationship reflect an underlying, latent goal system, the relative success of children in achieving the goal of preserving emotional security can be inferred from three measurable classes of response processes, including (a) emotional reactivity, characterized by intense, dysregulated, protracted forms of fear and distress in the face of interparental difficulties; (b) regulation of exposure to interparental conflict, characterized by elevated forms of avoidance of (i.e., flight responses) or involvement in (i.e., fight responses) the discord between parents; and (c) internal representations of the implications interparental difficulties have for the welfare of the self and family. Reflecting one component of the mutual interplay, threats to emotional security specifically trigger any number of responses within the three domains of responding (i.e., emotional reactivity, regulation of exposure to parent affect, and internal representations of family affect). Illustrating the reciprocal feedback system, the three classes of response processes are designed to preserve security through their regulative and monitoring functions in contexts of potential danger. For example, in high-conflict homes, elevated emotional reactivity may serve as affective “tags” that highlight potential danger and prime children to respond proactively to impending threat. Likewise, by providing children with maps of unfolding family processes that commonly proliferate into threatening events, negative internal representations of interparental relations assist children in scanning and responding quickly to impending stressors in the family. However, despite the proximal value of the three response classes in assisting children in monitoring and coping with threat, the prolonged operation of the emotional security system is proposed to have deleterious consequences in the long run by increasing children’s vulnerability to psychological problems (see Pathway 3 in Figure 1). Although addressing how interparental conflict directly affects children’s functioning is a central goal of emotional security theory, considerable conceptual emphasis has also been directed to contextualizing the study of children’s coping and adjustment to interparental conflict within the broader family system. Family processes are specifically postulated to alter the mediating role of emotional security through two primary pathways. First, Pathway 4a illustrates that interparental conflict also indirectly affects children’s trajectories of adjustment through its association with other family processes, including parenting difficulties (e.g., parental rejection, unresponsiveness) and family-level perturbations (e.g., family enmeshment, coparenting struggles). In one of the more prominent pathways in the model, the mediational role of parenting difficulties in associations between interparental conflict and child developmental trajectories is theorized to be further mediated by children’s attachment security in the parent–child relationship. In this process, the frustration, preoccupation, and distress stemming from bouts of interparental discord are postulated to undermine parental emotional availability

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in parent–child interactions and, over time, erode children’s attachment security or confidence in parents as sources of protection and support. Second, Pathway 4b further illustrates the hypothesis that mediational pathways among interparental discord, children’s emotional insecurity in the interparental relationship, and child developmental trajectories may vary as a function of family-level characteristics and attributes of children (e.g., temperament). In the role as protective or potentiating factors, these characteristics may serve to either magnify or dilute the deleterious consequences of interparental conflict and children’s difficulties in preserving security in the interparental relationship.

C. LIMITATIONS OF PRIOR TRANSLATIONS OF THE FUNCTIONALIST PERSPECTIVE IN EMOTIONAL SECURITY THEORY Judged in the context of the current state of emotional security theory, the common core of functionalist assumptions has been a useful tool for building a model of how emotions are organized to address and resolve specific challenges posed by interparental discord (Keltner & Gross, 1999). However, the original development of emotional security theory was explicitly grounded in an account proposed by Campos and colleagues (Campos et al., 1994; Campos & Barrett, 1984) that emphasizes understanding how the development and organization of emotions serve as solutions to problems in the current environment. Emotion is, therefore, “functional” in the sense that it is captured by how individuals modify person–environment transactions to achieve proximate goals. As Campos (1994) noted, “the approach is functionalist not because it deals with evolutionary survival value, but rather because it links emotion to what a person is trying to do (p. 1).” Subsequently, early formulations of emotional security theory minimized the role of ethology and evolution in outlining the emotional security system. For example, Cummings and Davies (1996) noted that, “Although the primary emphasis on the evolutionary/ethological origins of emotional security stressed by Bowlby (1969) may apply to the parent–child relationship, it is not readily extended to children’s derivation of emotional security from the quality of interparental relations, sibling relations, [and] general family functioning” (p. 129). Guided by this analysis, we further concluded that “a change in the conceptualization of emotional security as a goal is required for a family-wide perspective” (p. 129) (also see Davies & Cummings, 1998). However, not all functionalist accounts eschew ethological principles and evolutionary perspectives (e.g., Bretherton et al., 1986; Keltner & Gross, 1999). Functional accounts rooted in ethology and evolution underscore that emotions are phylogenetic vestiges of adaptive solutions to problems that promoted the survival and reproduction capacities of our ancestors. Even if emotions do serve

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as solutions to proximal challenges, ethological and evolutionary theories maintain that the structure and function of emotions were developed and shaped through natural selection as ways of resolving recurrent prehistoric challenges (Buss et al., 1998; Crawford, 1989; Ohman & Mineka, 2001; Tooby & Cosmides, 1990). From this perspective, simply focusing on the role of emotion in the context of current problems can be misleading because the architecture, organization, and function of any emotional–behavioral system developed over the evolutionary course of the species. Thus, examining the operation of emotional–behavioral systems in relation to proximal cues and ontogenetic history is insufficient without consideration of its interplay with phylogeny. The resulting implication is that considering the role of ethology in emotional security theory is not only theoretically viable but also may yield valuable insights into the process of further theory building. When specifically applied to the framework of emotional security theory, an ethological account would, therefore, call for a new look at how the function and sequelae of the goal-corrected system of security in the interparental relationship was shaped by natural selection and adaptations in the ecology or environment of evolutionary adaptedness faced by the long pedigree of our species. Consequently, our first step in shifting our theoretical emphasis is to address how an ethological perspective advances an understanding of the relations between security in the interparental and parent–child subsystems.

II. Distinctions between Security in the Interparental and Parent–Child Subsystems Emotional security theory makes the assumption that children experience threats to security in the interparental relationship in ways that are overlapping with, but still distinct from, attachment security in parent–child relationships. However, emotional security theory has failed to provide an account of the overlapping and unique properties of the two emotional security systems. Neglect of this issue stemmed, in large part, from the conceptual difficulty in reconciling the different principles of emotional security theory and attachment theory within a coherent framework. For example, original ethological perspectives of the attachment system underscored the child’s behavioral goal of proximity to the caregiver (Bell & Richard, 2000). Yet, in emotional security theory, no obvious parallel to the behavioral goal of proximity-seeking in the attachment system and its corresponding evolutionarily adaptive function (i.e., protection from harm) was identified for the child’s security system in the interparental relationship. Furthermore, at the time of the formulation of our theory, attachment theorists underscored the complementary role of a child’s psychological goal of felt-security in the control system along with the behavioral goal of proximity-seeking (Cicchetti et al.,

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1990; Sroufe & Fleeson, 1986; Sroufe & Waters, 1977). Thus, consistent with this trend, the original solution to the incompatibility of the behavioral systems was to adopt the functionalist perspective by Campos (1994) and strip emotional security theory of ethological influences in favor of focusing on a psychological or internal goal of felt-security in the interparental system. However, our contention here is that by failing to incorporate an ethological perspective in emotional security theory, significant difficulties arise in reconciling emotional security and attachment theory versions of security because they are based on fundamentally different theoretical principles embraced by functionalist and ethological perspectives. Over time, the tacit assumption that the two types of emotional security reflect different systems appears to have become so ingrained that no one, to our knowledge, has attempted to address formally and explicitly the central questions of how and why security in the interparental subsystem is distinct in its substance from security in the parent–child subsystem. A corollary of this neglect is a decisive shift away from providing a descriptive account of the nature of the interplay between the two systems. In the following sections, we show how restoring the role of ethology to its rightful place in models of emotional security may address these gaps and further advance emotional security theory.

A. THE ROLE OF ETHOLOGY IN ADVANCING THEORY ON THE RELATION BETWEEN TYPES OF SECURITY Using an ethological perspective as a guide, we believe that delving deeper into identifying the behavioral and mental products of evolution and natural selection might more effectively elucidate how and why security in the interparental relationship is similar to and different from attachment security in its composition. Within an ethological and evolutionary framework, distinct systems or modules of responding to environmental cues are postulated to have emerged and persisted based on their success in promoting survival (and ultimately reproduction) of the species in the context of intractable ecological challenges over evolutionary time (Ohman & Mineka, 2001; Tooby & Cosmides, 1990). Accordingly, the behavioral and mental processes of all, or virtually all, individuals within a species should be organized in relation to these modules. Each module or control system is also theorized to comprise integrated sets of biological, behavioral, and psychological components that operate efficiently and flexibly to achieve the goals relevant to the survival and reproduction of the species. Guided by this control systems framework, we postulate that a primary source of discrimination and convergence between the two types of security lies with how children’s transactions within different family relationship contexts (i.e., interparental and parent–child) trigger different configurations in the operation

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of adaptively evolved modules or systems. The basic premise of our reformulation is that emotional security in the interparental relationship overlaps with attachment security due to similarities in the activation of multiple control systems and corresponding behavior and mental processes. Yet, the distinctive nature of the two security systems is hypothesized to reflect differences in the comparative salience of the different control systems that stem from fundamentally different transactions between children and the interparental and parent–child subsystems.

B. ETHOLOGICAL ROOTS OF DIFFERENCES BETWEEN THE TYPES OF SECURITY Differences in the two security systems are particularly evident in the activation and integration of six different control systems, described in Table I, that are particularly relevant in childhood: (a) attachment, (b) affiliation, (c) exploration, (d) social defense (or fear/wariness), (e) dominance, and (f) caregiving systems (e.g., Bretherton, & Ainsworth, 1974; Gilbert, 1993; Hilburn-Cobb, 2004; Sloman et al., 2002; Stevenson-Hinde & Shouldice, 1993; Trower & Gilbert, 1989). Each of these control systems can be distinguished on the basis of adaptive functions, goals, and action tendencies or strategies (Hilburn-Cobb, 2004). The adaptive function is defined as the broad advantage the system or module conferred in promoting the survival of the species over evolutionary time. As shown in Table I, adaptive functions can vary from protection against harm to acquisition of basic materials for survival (e.g., food, shelter). The goal of each control system in Table I refers to the original specific function of the module in regulating the present relation between the organism and the environment in ways that ultimately contributed the survival and continuation of the species. Finally, action tendencies are characterized by specific behavioral strategies, affective mechanisms, and ways of processing information that serve to flexibly permit the achievement of the behavioral goal. In our ethologically influenced account of the nature of similarities and differences between the two types of security systems, felt-security is conceptualized as serving an overarching organizing goal for integrating control systems. Our model draws on the work of Hillburn-Cobb (2004) in asserting that the psychological goal of felt-security, while central to many modern derivations of attachment theory, is not simply confined to the attachment system. Rather, any number of control systems can be enlisted in the service of attainment and maintenance of felt-security. Figure 2 illustrates a conceptual representation of proposed relations between the goal of felt-security and the different control systems during childhood. Pathway 1 in Figure 2 denotes the locus of the nexus for the attachment security system and our specific postulation that a main source of attachment security

Attachment

Maximize sensitivity and protection of caregiver

Protection from harm

Social Defense

Defuse or avoid threats and aggression by conspecifics

Exploratory

Familiarization with physical world Acquire social skills and standing Proximity to the dependent

Distress; bids for comfort and support; proximity-seeking; clinging behavior; monitor whereabouts of caregiver Fear; distress; vigilance; freezing; flight; fight; cutoff behavior (e.g., covering eyes); camouflaging behaviors (e.g., inhibiting verbal and overt emotional expressions; concealing face); heightened perceptual–cognitive sensitivity to environmental signs of danger; long-term demobilization (i.e., dysphoria, vegetative state, fatigue, inferiority, hopelessness, and helplessness), social de-escalation strategies (e.g., gaze avoidance, coy behavior) Approach novel objects and settings; systematic observation and manipulation of object world Social interest and approach; initiation and maintenance of interpersonal ties Monitoring of dependent, sensitivity to dependent distress signals, and responsiveness to dependent needs Anger; aggression; attention-seeking; direct gaze

Affiliation Caregiving

Dominance

Increase access to material resources and mates, eliminate adversaries

Protection from harm

Access to basic survival materials Access to basic survival materials; formation of alliances Protection of dependents

Acquisition of basic survival materials

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TABLE I Descriptions of the Adaptive Functions, Observed Goals, and Common Strategies of Some of the Salient Control Systems in Childhood

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Internal Goal: Felt Security

1

Attachment System

Exploratory System

Affiliation System

2

Defense System

Caregiving System

Dominance System

Fig. 2. A theoretical representation of proposed interrelationships between the goal of felt-security in different family relationships and the multiple control systems during childhood.

revolves around the interplay among the internal goal of felt-security and the attachment control system. Under conditions of internal (e.g., fatigue, sickness) or external (e.g., darkness, aloneness, quickly approaching or looming stimuli) cues to danger or stress, the behavioral goal of the attachment system is to increase access to a supportive, protective caregiver (Ainsworth, 1969; Bowlby, 1969; Cassidy, 1999), which is theorized to increase the fitness of humans by providing a source of protection against danger for children. As part of the control system, children have access to a large repertoire of behaviors that facilitate the achievement of the behavioral goal. For example, proximity and clinging behavior, verbal bids for comfort and support, distress expressions, and regular monitoring of the whereabouts of the caregiver are all potential means toward increasing access to a supportive caregiver (Bowlby, 1969; Hilburn-Cobb, 2004). In contrast, Pathway 2 in Figure 2 denotes that emotional insecurity in the interparental relationship is primarily nested within a system characterized by the interplay between the social defense (or the submissiveness or subordinate) system and the felt goal of emotional security. Thus, our contention is that children’s emotional security in the interparental relationship is primarily regulated by the activation of the child’s defense system when exposed to interparental conflict. It could be suggested that bouts of conflict or discord between parents are regarded by children as external threats that activate the child’s attachment system to provide a buffer against potential harm. However, we believe that the attachment system is unlikely to be the main control system underlying emotional

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security in the interparental relationship because the frightening and frightened behavior exhibited by parents during these conflicts is proposed to inhibit the salience of the attachment system. In other words, relationship difficulties between caregivers pose a dilemma for children in that caregivers, who are commonly the source of protection and solace through the operation of the attachment system, are simultaneously a cause for alarm and threat through their expressions of hostility, distress, and emotional volatility during interparental disputes. Thus, the primary solution to protect oneself against harm in the face of this dilemma may be the activation of the defense system. As shown in Table I, the defense system shares with the attachment system the adaptive function of safeguarding against threat (Marks & Nesse, 1994). However, unlike the attachment system, the external or observed goal of the social defense system is minimizing or neutralizing conspecific threat. The specific behaviors designed to achieve this external goal and, ultimately, the internal goal of felt-security, strongly resemble the three affective–behavioral component processes of security outlined in emotional security theory. More specifically, fear, vigilance, freezing, and distress are characterized as key aspects of the emotional reactivity component in our original outline of the goal-corrected system of security (Davies & Cummings, 1994). Likewise, flight, fight, cutoff, camouflaging, and long-term demobilization behaviors within the ethological social defense system correspond to the avoidance and involvement strategies within the regulation of exposure to interparental relations component of our security system. These proposed distinctions between attachment and emotional security systems on the basis of their primary relation to different control systems must also be translated into testable hypotheses. Although some behaviors such as distress and monitoring the whereabouts of caregivers simultaneously serve both attachment and social defense systems, specific behaviors that more consistently serve one system as opposed to the other could provide a rich foundation for hypotheses. Building on this foundation, one implication is that exposure to interparental conflict should yield a relatively higher incidence of patterns of fear, vigilance, freezing, flight, cutoff, camouflaging, and social de-escalation behaviors compared to behaviors that are primarily organized around the attachment system (e.g., bids for support, proximity-seeking, clinging). Testing these novel hypotheses will also hinge on collecting descriptive data drawn from observations and analysis of children’s responses to interparental conflict. Diary and observational assessments of interparental conflict have been undertaken in some cases (e.g., Cummings et al., 2002; Cummings, GoekeMorey, & Papp, 2004; Cummings, Zahn-Waxler, & Radke-Yarrow, 1981; Davies et al., 2006a; Garcia O’Hearn, Margolin, & John, 1997). However, the main units of analysis in these investigations have generally been confined to broad emotional (e.g., fear, anger, distress) and behavioral (e.g., involvement) variables

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that do not readily correspond to attachment and defense constructs in ethological theory. Therefore, these measurement and data analysis strategies do not yield attachment and defense variables necessary to authoritatively tease out the behavioral patterns associated with each of the control systems. Interpreted with this important qualification in mind, findings from earlier studies provide some tentative support for our predictions. For example, maternal and paternal reports in daily home diaries reveal a relatively high percentage of children who exhibit flight, fear, and intervention behaviors during conflicts between parents (Garcia O’Hearn et al., 1997). However, the lack of comparable assessments of behaviors relevant to the attachment system precludes any analysis of the relative propensity of interparental conflict to activate the two systems. Any future comparisons of the behaviors of the two systems must also carefully craft a design to capture characteristics of the interparental relationship that are proposed to activate the defense system in our theory. Specifically, the defense system is theorized to be primarily activated when parents display frightening (e.g., hostility, aggression, threats, yelling) or frightened (e.g., fear, cowering, freezing) behavior in their conflicts. Thus, comparing patterns of attachment and defense behavior in the context of constructive forms of conflict between parents does not provide a sufficient test of the hypotheses. Consistent with this hypothesis, Garcia O’Hearn et al. (1997) reported that children exposed to physical violence between parents were most consistently apt to leave the room and display fear or sadness than were children exposed to low or verbally aggressive conflict.

C. ETHOLOGICAL ROOTS OF SIMILARITIES BETWEEN THE TYPES OF SECURITY Any account of the differences between the security systems must also be balanced by a consideration of the similarities. The attachment and defense systems do not operate in isolation from each other. Rather, as illustrated by the bidirectional arrows in Figure 2, they are tethered with each other and other control systems by the overarching goal of felt-security which, more specifically, reflects a homeostatic condition characterized by the successful coordination of emotional, cognitive, and neurobiological regulation (Hilburn-Cobb, 2004). Given their ties with each other, qualitatively different patterns of behavior would also be hypothesized to emerge from the interplay of the defense and attachment systems. Although the parent–child attachment system, at an evolutionary level, is geared toward reducing threat to children by drawing them toward caregivers in times of stress, this tendency is counteracted by the frightening and frightened behaviors exhibited by distressed caregivers during episodes of interparental discord. Thus, the natural basis for allaying fear in conflict situations is also a source of their threat (Lyons-Ruth & Jacobvitz, 1999).

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The virtual “draw” between attachment and defense systems is theorized to produce the prevalence of freezing, bizarre, aimless, and overtly contradictory behaviors (e.g., simultaneous or sequential approach and avoidance displays toward the angry caregivers) during interparental conflict. These response patterns may be commonly interpreted as signs of disorganized, disoriented (i.e., type D) attachment in parent–child contexts. However, we maintain that they also provide telling information about threats to children’s emotional security in the interparental relationship because the reaction pattern is the direct product of the defense system in response to interparental conflict. The attachment system, in this context, is a secondary strategy of achieving security that serves the more prominent defense system and its role in achieving felt-security in the interparental subsystem. Accordingly, though we propose that the achievement of felt-security in the interparental and parent–child attachment relationships is rooted in different ethological control systems (i.e., defense, attachment), the mutual interplay between the two systems is likely to yield similarities in some profiles of security across the interparental relationship and parent–child attachment relationship. The remaining bidirectional arrows among the systems in Figure 2 reflect the constant coordination of the attachment and defense systems with the other control systems. For example, the exploratory and affiliation systems evidence a dialectical relation with the attachment and defense system (Ainsworth, 1972; Cassidy, 1999). The natural curiosity to explore the physical and social world within the exploratory and affiliation systems shares the adaptive function of acquiring knowledge and skills about the environment necessary for basic survival (see Table I). However, exploration without balanced appreciation for potential danger was likely to result in significant reductions in survival advantage over evolutionary time. According to evolutionary theory, the consequence of this adaptive problem was the smooth coordination of the attachment and defense systems with the exploratory and affiliation systems. Commonalities in the interdependency between the attachment and defense systems and these other systems provides another basis for expecting similarity in the elements of the response patterns underlying attachment security and emotional security. For example, reductions in exploration, play, and sociability commonly signify activation of the defense system and, in certain configurations, perturbations in the attachment system. Reflecting the conjoined nature of the defense system with exploratory and affiliation systems, social withdrawal (e.g., social unresponsiveness or disinterest) and disruption in the child’s natural exploratory and play activities (e.g., preoccupation) in response to interparental conflict are regarded as potential signs of insecurity in the interparental relationship. Thus, evaluating attachment security and emotional security in the interparental relationship is facilitated by the respective analyses of the attachment and defense control systems within the broader organization of the other control systems.

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The bidirectional pathways between the attachment and defense systems and other control systems in Figure 2 also underscore that children may resort to other secondary strategies for achieving felt-security in family relationships when the more direct strategies within attachment and defense systems are ineffective. The predominant reliance on middle class samples in the Western world does not adequately capture the normative threat, suffering, and danger faced by the vast majority of children in the world in contemporary times or throughout our ancestral history (Crittenden, 1999). Preservation of safety and security under varied environmental niches is likely enhanced through flexible enlistment of the lower-order systems when defense or attachment systems do not provide sufficient solutions to the problem (see Figure 2). Thus, patterns of attachment security can be derived from individual differences in the propensity of children to co-opt other control systems in the service of the attachment system and its respective external and internal goals of gaining access to a protective caregiver and the attainment of felt-security (Hilburn-Cobb, 2004). For example, hostile, aggressive behavior within the dominance system may be recruited as a secondary strategy to achieve some modicum of felt-security in the face of significant perturbations in the attachment system (e.g., Crittenden, 1992, 1995; HilburnCobb, 2004). Similarly, attaining felt-security in the interparental relationship under conditions of extreme ecological threat, prior experiential histories, proximal characteristics of the child, or some combination thereof may require more than simply the efficient activation of the defense system. Therefore, patterns of insecurity in the interparental relationship may be gleaned from response processes of the defense system and other systems recruited to support children’s coping with threat in the interparental subsystem. In summary, we propose that an ethological perspective provides cogent justification for explicating the nature of the relation between attachment security in the parent–child subsystem and security in the interparental subsystem. Distinctions between the types of security are proposed to be rooted in different underlying goal-corrected control systems. Whereas individual differences in attachment security in the parent–child relationship are theorized to reflect, in large part (but not exclusively), variations in the operation of the attachment system, differences in security in the interparental relationship are posited to result primarily from the operation of the defense system. Similarities in patterns of responding between the two types of security are hypothesized to result from (a) the common overarching goal of felt-security, (b) overlap in how mental and behavioral patterns facilitate the achievement of behavioral or external goals within control systems, and (c) comparability in the interrelationships among the defense and attachment systems and other control systems (e.g., exploration, affiliation). In the next section, we take our ethological analysis of the emotional security system one step further by explicating the implications of the social

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defense system for identifying individual differences in children’s emotional security in the interparental relationship.

D. TOWARD A PATTERN-BASED APPROACH TO EMOTIONAL SECURITY IN THE INTERPARENTAL RELATIONSHIP Developing a formal, ethologically based system for identifying patterns of insecurity in the interparental relationship is premature at this early stage of theory development. However, some of the potentially prominent patterns of security may be posited in rough outline. If security in the interparental relationship is closely intertwined with the defense system, then response patterns indicative of prolonged activation of the defense system may be one of the predominant profiles of insecurity in the interparental relationship. As Table II shows, this may result in a multiplicity of different strategies that are activated by innate rules or algorithms based on the nature of the threat (Gilbert, 2000, 2001). A primary insecure pattern of organizing responding in the face of destructive interparental conflict is hypothesized to consist of prolonged use of more basic mobilizing strategies that are shared between the social defense and the nonsocial (e.g., predatory) defense systems, including elevated distress, freezing, perceptual sensitivity to threat in the family unit, and flight or fight (i.e., involvement) behavior (Gilbert, 2000; Johnston & Roseby, 1997; Marks & Nesse, 1994; Ohman & Mineka, 2001). Given the mutual, dialectical relation between the defense system and the exploration and affiliation systems, chronic reductions in ongoing, developmentally salient activities (e.g., play in childhood) and interpersonal interactions should also be evident. Despite the dearth of research designed to identify profiles of reactivity to interparental conflict (Cummings & Davies, 2002), there is some support for the prevalence of the mobilizing-insecure profile. For example, Davies and Forman (2002) identified a “preoccupied” group of children who experienced a pattern of responding characterized by high levels of distress, involvement or avoidance, and negative appraisals and interpretations of interparental conflict for themselves and the family. Although the prolonged activation of the defense system may correspond to a preoccupied style of responding to interparental conflict, the flexibility of the control system is reflected in the use of other defensive subroutines for preserving felt-security. A second primary reaction pattern may involve the use of camouflaging strategies characterized by the effortful deactivation of overt expressions of fear and distress and regulation of distance from parents despite experiencing high levels of subjective alarm and apprehension (Gilbert, 2001; Marks & Nesse, 1994; also see Table I). In accordance with our camouflaginginsecure category, emotional security theory has proposed an insecure profile of

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Ecological and developmental conditions

Negligible to mild hostility Resolution Postconflict harmony

2. Mobilizing

Hostility Verbal aggresion Conflict escalation Child-related

Inhibitory control Planning/working memory Soothability Low negative affectivity Negative affectivity Shyness Perceptual sensitivity Poor soothability

3. Camouflaging

Hostility Verbal aggression Physical violence Conflict escalation Child-related Hostility Verbal aggression Poor resolution Disengagement

Family harmony Parental warmth Parental emotion coaching Secure parent–child attachment Family enmeshment Moderate parental warmth Parent psychological control/criticism Inconsistent parental care Resistant parent–child attachment Family instability, violence Parental abuse potential Parental rejection Parental intolerance of affect expression Disorganized attachment Family disengagement Parental unresponsiveness/apathy Parent depressive symptoms Parental criticism Protracted family adversity Family disengagement Lax discipline Parental unresponsiveness/apathy Parental neglect and abuse Avoidant attachment Family enmeshment Parental psychological control Severe parental psychopathology Poor parental limit setting and guidance Parent neglect Parental support seeking

4. Demobilizing

5. Dominant

Hostility Verbal aggression Poor resolution Disengagement

6. Caregiving

Hostility Verbal aggression Physical violence Inept, vulnerable displays Dysphoria, crying

Negative affectivity Shyness Perceptual sensitivity Inhibitory control Negative affectivity Shyness Poor working memory Poor soothability Negative affectivity High impulsivity Poor inhibitory control Poor working memory Poor perceptual sensitivity High negative affectivity Working memory Inhibitory control Perceptual sensitivity

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TABLE II A Summary of the Putative Family and Developmental Conditions Predicting the Social Defense Strategies for Achieving Security

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responding to interparental conflict characterized by low levels of overt displays of distress and involvement, elevated avoidance, and high levels of subjective feelings of distress and negative appraisals of interparental conflict (Davies, Winter, & Cicchetti, 2006b). Preliminary research on adult anger provides some support for the existence of this profile (e.g., Cole, Michel, & Teti, 1994; Cummings, 1987; Cummings & El-Sheikh, 1991; Davies et al., 2006b; Maughan & Cicchetti, 2002; Shipman et al., 2000), but more research is needed to draw more definitive conclusions. Analysis of the large repertoire of strategies available in the control system also raises the likelihood of the existence of undiscovered patterns of insecurity (see Gilbert, 2000, for more details). For example, evolutionary perspectives suggest that the use of long-term demobilization strategies characterized by disengagement, worry, dysphoria, anhedonia, self-blame, lethargy, helplessness, and hopelessness in the face of interparental conflict may coalesce into a demobilizing-insecure pattern (see Table I; also Gilbert, 2001; Gilbert & Allan, 1998; Marks & Nesse, 1994; Sloman et al., 2006). However, prior studies that were designed to capture individual differences in the organization of children’s response patterns to conflict failed to disentangle signs of demobilization (e.g., dypshoria, disengagement, coy or ingratiating behavior, appraisals of hopelessness) from other higher-order composites of emotional reactivity, involvement, avoidance, or negative internal representations. Therefore, identification of the presence and prevalence of this demobilizing-insecure pattern of responding hinges on more fine-grained measurements of children’s reactivity to interparental discord. In addition to proposing that groups of insecure children may largely be identified by individual differences in the operation of defense system (see Table I), Figure 2 specifically illustrates two other potential patterns of insecurity in the interparental relationship. The first possibility, depicted by the bidirectional arrow between the defense and the dominance systems, is that strategies within the dominance system may be solicited in the service of the defense system and the goal of attaining felt-security in the interparental relationship (Gilbert, 2001; Hilburn-Cobb, 2004; Marks & Nesse, 1994). Consistent with the other insecure patterns, children exhibiting a dominant-insecure pattern of responding are posited to show signs of wariness and fear indicative of the workings of the defense system. However, the dominant system and its accompanying anger and aggression are designated to help overcome the threat. Subjective feelings of vulnerability (e.g., fear, worry) and hypersensitivity in processing danger cues are hypothesized to be effortfully suppressed by the enlistment of the dominance system. Minimizing the experience of fear, distress, and worry may help sharpen the focal activity of defeating threats through aggressive displays (Dixon, 1998; Gilbert. 1993). Consequently, a dominant-insecure pattern of insecurity may be exhibited by: (a) noticeable expressions of overt distress and anxiety that reflect

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a high degree of ambivalence between fight and flight tendencies; (b) elevated hostility, anger, aggression, and loss of self-control; and (c) relatively low levels of subjective distress and appraisals of threat in the face of interparental conflict. Comparable patterns of responding to interparental or interadult conflict have been identified in prior research. For example, Cummings and colleagues identified a group of “ambivalent” children who exhibited high levels of behavioral distress and aggression in response to adult anger and low levels of subjective negativity and impulses to intervene or avoid the anger (e.g., Cummings, 1987; Cummings & El-Sheikh, 1991; El-Sheikh, Cummings, & Goetsch, 1989; Maughan & Cicchetti, 2002). Likewise, Davies and Forman (2002) identified a group of “insecure-dismissing” children who displayed overt signs of elevated behavioral distress and dysregulation (e.g., aggression, yelling) in conjunction with low levels of subjective distress and threat. However, thoroughly exploring the correspondence between our proposed dominant-insecure pattern and these earlier classifications of children’s reactivity to adult conflict will require sharper measurement batteries tailored to an ethological perspective. The bidirectional pathway between the defense and the caregiving systems in Figure 2 also suggests the possible occurrence of another insecure pattern. Although the caregiving system is theorized to reach full maturation during adulthood when care and protection of offspring is a stage-salient task (Bell & Richard, 2000), childhood and adolescence can be viewed as important training periods for acquiring caregiving skills and strategies (Hilburn-Cobb, 2004). Thus, the defense system may become coupled with the precocious activation of the caregiving system under some adverse family conditions. Children exhibiting an insecure-caregiving pattern of responding to interparental difficulties are theorized to exhibit high levels of distress, fear, and preoccupation with the activation of the defense system as well as high levels of involvement in interparental problems that require considerable forethought, concern, and even risk on the child’s part. Role reversal or parentification is one possible result as children take on the caretaking role of their dependent parents by acting as a confidante, therapist, and mediator for one or both of the parents (Davies, 2002). Clinical and empirical work has documented the occurrence of destructive forms of parentified involvement in high-risk families in which children engage in excessive, developmentally inappropriate emotional caretaking responsibilities (Byng-Hall, 2002; Jurkovic, 1998; Jurkovic, Morrel, & Thirkield, 1999; Solantaus-Simula, Punamaki, & Beardslee, 2002). For example, cluster analyses of children’s responses to parental negative moods yielded a group of “emotionally overinvolved” children who reported elevated fear and distress, while assuming the formidable responsibility of comforting and seeking help for the parents (Solantaus-Simula et al., 2002). As a final example, a secure pattern of responding to interparental conflict may be characterized by the efficient operation of the defense system. Even though

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conflicts between parents from time to time may increase the operation of the defense system and its accompanying displays of fear and distress, secure children can be distinguished from insecure children by their well-regulated, mild forms of concern and distress. For example, Davies and Forman (2002) identified a group of secure children who exhibited mild and relatively brief bouts of reactivity to conflict that were characterized by low levels of emotional reactivity, avoidance, involvement, and negative internal representations of interparental relationships across two studies. Although many of these children experienced some distress, concern, and impulses to intervene in parental conflicts, the broader organization of well-regulated responding and high levels of confidence in parents to manage disputes in ways that maintain family harmony suggests that the distress is organized around empathetic concern for the parents rather than defense and self-preservation. Confidence in the identification of a secure profile is bolstered by its close resemblance to the empirical delineation of “concerned” patterns of responding to anger between adults (e.g., Cummings, 1987; El-Sheikh et al., 1989) and “active empathy” patterns of responding to negative parental moods (Solantaus-Simula et al., 2002).

III. Family Origins and Correlates of Emotional Security Another litmus test in judging the value of ethology for emotional security theory is to examine its capacity to identify the family correlates and origins of individual differences in security in the interparental relationship. Toward this goal, Pathway 2 in Figure 1 depicts that repeated exposure to interparental conflict characterized by elevated hostility, indifference, and difficulties resolving anger progressively undermines children’s emotional security in the interparental relationship as manifested in greater emotional reactivity, regulation of exposure to interparental difficulties, and negative internal representations of interparental relations. This prediction is rooted in the sensitization hypothesis, which is shared with multiple theories of family conflict (e.g., Crockenberg & Langrock, 2001; Davies & Cummings, 1994; Grych & Fincham, 1990). According to this hypothesis, children’s exposure to destructive interparental conflict progressively increases their distress, negative cognitions, and coping difficulties in the face of conflicts over time. Consistent with the sensitization hypothesis, children’s experiential histories of witnessing angry, unresolved conflicts are associated with greater levels of subjective negative affect, behavioral signs of distress, and negative representations of interparental relationships, in subsequent conflicts between parents or other adults (Davies et al., 2002; El-Sheikh, 1997; Garcia O’Hearn et al., 1997; Grych, Seid, & Fincham, 1992). Supporting the central role of sensitization to interparental adversity in children’s coping, significant associations between interparental discord histories and children’s social and

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affective responses to conflict remain even when the proximal parameters of conflict in assessments of child reactivity to conflict are held constant (Davies & Cummings, 1998; Duggan, O’Brien, & Kennedy, 2001; Grych, 1998; Grych, Wachsmuth-Schlaefer, & Klockow, 2002). However, beyond this general hypothesis, little headway has been made in increasing the specificity and precision of predictions about the relation between experiential histories with properties of interparental interaction and the component processes of emotional security. As a consequence, important issues necessary for theoretical progress remain unaddressed. First, what are the specific dimensions or patterns of responding that are set in motion by destructive interparental conflict? Second, are there specific stimulus characteristics of interparental conflict that are particularly potent in engendering insecurity and the activation of the underlying defense system? Third, what is the underlying nature of the relation between exposure to destructive interparental conflict and signs of children’s emotional insecurity? Finally, what interparental family processes may affect the development of individual differences in broader patterns of insecurity in children? In the following sections, we address how ethology and evolution may provide significant leads in answering these questions.

A. THE NATURE OF THE INTERPLAY BETWEEN INTERPARENTAL CONFLICT AND CHILDREN’S REACTIVITY TO CONFLICT The sensitization hypothesis and its incarnations in family conflict theories leave open several qualitatively different interpretations for the development and course of the relation between interparental conflict and child reactivity to conflict. Evolutionary and ethological explanations of the operation of the defense or fear module provide two useful conceptualizations for sharpening our understanding of the relation (Ohman & Mineka, 2001). First, as a narrower, more specific formulation than the sensitization hypothesis offered in the family conflict literature, the selective sensitization hypothesis within evolutionary psychology specifically proposes that arousal or provocation under stressful conditions serves to prime defense responses (e.g., fear) to threatening stimuli in the environment. The selective component of the hypothesis refers to the notion of a genetic or biological disposition to respond to specific stimuli that were significant threats to survival (e.g., angry faces), whereas the sensitization component of the hypothesis suggest this biological disposition to respond with fear to specific stimuli is only amplified by an existing state of arousal or threat. No prior history of learning or conditioning is necessary. Instead, the process is characterized by arousal or co-occurring stressful conditions that prime the defensive responses to stimuli that signified threats (e.g., angry faces) in typical environments over evolutionary time (Gray, 1987; Lovibond, Siddle, & Bond, 1993).

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Translated to the study of interparental conflict, the selective sensitization hypothesis would postulate that children exposed to high levels of destructive conflict experience progressively more distress and reactivity to subsequent conflict because they are more likely to be in a preexisting, temporary state of arousal or fear by virtue of their exposure to contemporaneous family conflict. Learning or conditioning is not the process that leads children to become increasingly vigilant in the context of destructive interparental conflict. Rather, history of exposure to interparental conflict is a distal variable indirectly associated with greater reactivity to conflict through its co-occurrence with a constellation of family stressors and its resultant effect on increasing the threat, arousal, and reactivity to conflict. Second, the selective association or preparedness model is comparable to the selective sensitization hypothesis in assuming that evolution has forged a legacy that results in a constitutional bias toward processing and reacting to certain environmental cues (e.g., angry faces) with fear. However, in contrast to selective sensitization, the “association” component of the model suggests that some form of learning is the operative mechanism underlying the effects of greater exposure to interparental conflict (Hofmann, Moscovitch, & Heinrichs, 2004). Tests of the viability of this theory in the link between interparental conflict and increased child reactivity to conflict must, however, be sensitive to the multitude of underlying response processes proposed within different versions of the selective association model. For example, repeated exposure to stressful events such as interparental conflict may result in sensitization in neurobiological mechanisms, including increased reactivity of excitatory neurotransmitters and stress hormones such as norepinephrine, dopamine, and corticotrophin-releasing factor (e.g., Monroe & Harkness, 2005; Post, 1992). Likewise, social-cognitive formulations might translate to the hypothesis that schemas comprising constellations of cognitions (e.g., perceived threat) and affect (e.g., fear) become increasingly integrated and coupled together with repeated exposure to stressful interparental events (e.g., Segal, Williams, Teasdale, & Gemar, 1996). From this perspective, sensitization is conceptualized as a product of progressively greater reciprocal influences among multiple dimensions of negative responding as children are repeatedly exposed to interparental conflict (see Monroe & Harkness, 2005, for other models). Although the tenets of the sensitization model proposed within the interparental conflict literature are more closely linked with evolutionary versions of the selective association hypothesis than the selective sensitization hypothesis, no studies have systematically examined the relative potency of the various mechanisms that are proposed to mediate the sensitization process across the models. Moreover, concurrent arousal processes in the selective sensitization model and the biopsychological changes resulting from histories with parental conflicts in the selective association model may both account for a proportion of the sensitization process.

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For example, Cummings and Zahn-Waxler (1992) proposed that history of exposure to interparental conflict may lead to persistent arousal and emotional dysregulation under certain conditions (also see Zillmann, 1983). Despite suggesting mechanisms underlying the vulnerability of children exposed to interparental conflict, ethological accounts are vague in generating hypotheses about the form of the relation between interparental conflict and children’s reactivity. It might be assumed that the sensitization process follows, at least in rough form, some dose–response relation. However, if human response systems are guided by a complex set of algorithms to cope with the multiplicity of prehistoric environmental niches (Klein et al., 2002), then the association between interparental conflict and child reactivity may not be linear in form. For example, the challenge model in developmental psychopathology specifies that stressful conditions, especially in small or moderate doses, may actually have “steeling” effects that enhance coping and adjustment and inoculate individuals against subsequent psychological insult (Garmezy, Masten, & Tellegen, 1984; Rutter, 1985, 1987), particularly when the aversive consequences following the challenge are minimal or easily avoided (Nesse, 2005). By extension, exposure to destructive interparental conflict may trigger children to develop more effective skills for coping and adjusting to adversity if bouts of conflict are relatively infrequent. As another illustration, the stress autonomy model is consistent with the selective sensitization and association models in its hypothesis that greater exposure to stressors such as destructive interparental conflict may progressively increase children’s reactivity to subsequent bouts of problems between parents in the early stages. However, it diverges from the earlier models by suggesting that over longer periods of time, interparental conflict may set in motion other mechanisms that supersede the direct risk conferred by interparental conflict on children (Monroe & Harkness, 2005). Therefore, following a dose–response relation between interparental conflict and child conflict reactivity in the early stages of exposure, the curvilinear nature of the relation may be evident in an asymptote signifying progressively weaker associations between interparental conflict and child functioning in latter stages of exposure. In summary, documenting the form of the relation (e.g., linear, curvilinear) between interparental conflict and children’s reactivity to conflict still requires further research.

B. SELECTIVITY IN THE SENSITIZATION PROCESS: STIMULUS CHARACTERISTICS OF INTERPARENTAL CONFLICT Only destructive forms of conflict between parents are hypothesized to undermine children’s security in the interparental relationship, but destructive ways of expressing conflict vary widely. Whereas some couples may display their discord through physical violence, other couples may engage in bouts of verbal aggression

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(e.g., insults) or yelling. Discord in other couples may manifest itself in disengagement, indifference, withdrawal, sulking, dysphoria, or the silent treatment. Subsuming different forms of conflict under a broad definition of destructive conflict provides an insufficient base for sharply identifying how conflict threatens children’s emotional security. How might a focus on evolution allow us to identify destructive forms of conflict more precisely? Many evolutionary models of the evolved adaptive defensive system or module share the assumption that humans are biologically or genetically predisposed to respond in fearful and defensive ways to specific stimuli that were significant threats to our ancestors’ survival (Lovibond et al., 1993; Ohman & Mineka, 2001; Seligman, 1971). Cues evoking genetically primed fear responses can range from very specific interspecies (e.g., moving sinusoidal shapes indicative of snakes) and intraspecies (e.g., angry human faces) stimuli to more abstract, but nonetheless potentially dangerous, stimuli (e.g., loud noises; fast-approaching or looming objects or organisms) (e.g., Bowlby, 1969; Hofmann et al., 2004; Marks & Nesse, 1994). Of these, intraspecies stimuli are particularly relevant for identifying specific elements of interparental conflict that are particularly threatening to children. More specifically, the selective, biologically hard-wired, sensitivity of the defense module to angry faces corresponds more closely with the hostile, angry, and aggressive patterns of interparental conflict than the more dysphoric, withdrawn, and indifferent categories of conflict. Likewise, the ability to decipher fearful expressions among conspecifics holds particular adaptive significance as another mechanism for detecting environmental peril. Accordingly, witnessing anger or fear among conspecifics, especially two attachment figures, may be particularly likely to pose a threat to children’s emotional security and, over time, their psychological and physical well-being. However, an evolutionary perspective does not necessarily relegate dysphoric or disengaged forms of conflict to an insignificant status as risk factors. Many evolutionary models propose that social-cognitive mechanisms were incorporated onto the preexisting template of the fear or defense module and served important adaptive functions for coexisting safely in groups or families of conspecifics (described in the next section). These social-cognitive mechanisms are proposed to yield algorithms for identifying the probability of deleterious consequences of various interpersonal interactions within social groups (Hofmann et al., 2004). In evolutionary models, dysphoria and disengagement signify abandonment, rejection, and interpersonal struggle within the social hierarchy (Gilbert, 2001). Therefore, repeated exposure to these conflict properties may undermine children’s security in the interparental relationship (Dixon, 1998). However, given evidence supporting a biological proneness to respond defensively to conspecific anger and fear (Ohman & Mineka, 2001), it follows that exposure to parental hostile and fearful displays during conflict should be a more prominent risk factor in undermining children’s sense of security.

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The dearth of research designed to carefully contrast children’s reactions to interparental hostility and fear with other dimensions of conflict (e.g., dysphoria, disengagement) make it difficult to draw any conclusions about the viability of this hypothesis. Some notable studies have begun to discriminate between different forms of conflict and their implications for children’s coping and reactivity. However, in the few studies that distinguish hostile or fearful expressions of conflict from other forms of conflict between parents, the analyses failed to test directly the conditions necessary to test our hypothesis (e.g., Cummings et al., 2002; Davies et al., 2006a). Complicating the empirical task of disentangling the impact of types of interparental conflict are findings indicating that some forms of conflict (e.g., disengagement) are natural outgrowths of prior forms of conflict (e.g., hostility) in the deterioration of adult relationships (Katz & Woodin, 2002). Moreover, as we document in the next section, the greater potency of some forms of conflict to undermine children’s emotional security may be limited to specific domains of child responding.

C. DOMAINS OF CHILD REACTIVITY IN THE FACE OF INTERPARENTAL CONFLICT Evolution and ethology also point to the significance of considering the multidimensional properties of interparental conflict in tandem with the plurality of response processes in the social defense system. Survival hinged on the evolution of a fear module designed to rapidly prioritize recurrent environmental threats and supplant the salience of any competing or interfering processes (Hofmann et al., 2004; Ohman & Mineka, 2001). Rapid reactivity to threatening cues is specifically achieved through the direct, automatic levels of processing that are outside the conscious awareness of the organism (i.e., automaticity), whereas the ability of the fear module to resist potential input from other systems (including conscious processing) in processing the threat indicates encapsulation. By design, these criteria point to the identification of neural circuitry for processing threats that are specialized, resistant to the influence of other processes, and located in the more ancient structures of the brain. Indeed, considerable research supports the automaticity and encapsulation of the processing of cues deemed to pose considerable threat to humans during evolution, including processing of aversive conspecific stimuli (i.e., angry faces) relevant to the social defense system (Ohman & Mineka, 2001). Complementing these findings is neurobiological evidence for the role of the amygdala in the processing of fear-relevant stimuli (Rothbart & Posner, 2006). The amygdala is a limbic structure located in the phylogenetically older regions of the brain. It is regarded as a primary neural structure that rapidly processes input for emotional significance and fear relevance through multiple pathways

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(Amaral et al., 2003; Barrett & Wager, 2006). In one of these pathways, perceptual input appears to bypass the neocortical regions of the brain, thereby leading to rapid, unrefined processing of potential fear stimuli that is relatively resistant to cognitive awareness or control (LaFreniere, 2005; LeDoux, 1996). The identification of other pathways involving the amygdala further supports the automatic and encapsulated nature of fear-processing stimuli in the limbic system. The amygdala sends more information to the cortex than it receives. A common conclusion of these findings is that fearful reaction patterns tend to regulate cognition (e.g., appraisals, expectancies) more strongly than cognition regulates fearful affect (for more detailed neurobiological accounts, see LeDoux, 1996; Ohman & Mineka, 2001). What are the implications of automatic and encapsulated processing of threatening cues for advancing emotional security theory? One proposition is that it helps to bolster the underlying foundation for emotional security theory. Although the conceptual premium placed on children’s automatic patterns of responding to interparental conflict is a key characteristic that distinguishes emotional security theory from other theories of interparental conflict (Davies et al., 2006b), evidence for this assumption was restricted primarily to qualitative accounts of how processes evolving from rudimentary sensorimotor systems of children may develop into stable patterns of child reactivity in high-conflict homes (Davies et al., 2006b; Johnston & Roseby, 1997). Moreover, these clinical accounts were limited largely to infancy and the preschool years, raising questions about the applicability of the conceptualization to broader developmental periods. In contrast, evolutionary analyses provide compelling empirical evidence for the automatic, encapsulated nature of the social defense system across broader developmental periods. In our theory, automaticity and encapsulation are reflected in scripts that, in the words of Johnston and Roseby (1997) “can initially be formed from schema of preverbal and perceptual experience … long before the child has access to language to encode the experience” and, as a result, “frightening scenes of family conflict and violence may never be available for cognitive recall but can continue to manifest themselves in scary dreams and anxious feelings” (p. 59). However, our reformulation builds on the framework of Johnston and Roseby (1997) by maintaining that automatic and encapsulated fear components of the social defense system may evidence plasticity across broader developmental periods than early childhood. Our evolutionary-based reformulation emphasizes unconscious or semiconscious components of the emotional security system and thereby distinguishes our theory from other theories in its exposition of the unfolding sequence and interplay of children’s responses to interparental conflict. The other established theories of interparental conflict—the cognitive–contextual framework (Grych & Fincham, 1990) and specific emotions theory (Crockenberg & Langrock, 2001)— both posit that children’s cognitive appraisals of an interparental conflict event

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mediate the link between that event and their emotions. Thus, as a first response, cognitive appraisals, which are largely (i.e., specific emotions theory) or exclusively (i.e., cognitive–contextual framework) accessible to consciousness, produce and regulate the subsequent course of affective responses to and coping with the conflict. Emotional security theory differs from these theories in operating from the evolutionary premise that fearful affect plays a more primary role as a cause than a consequence of cognition in the defense system (Ohman & Mineka, 2001). In the first step of the process shown in Figure 3, exposure to an episode of destructive interparental conflict is theorized to activate the security system by eliciting affective–physiological reactions that are largely reflexive and outside the awareness of the child. Reactivity to the threatening interparental event may therefore initially develop into relatively automatic, primitive expressions of fear, distress, freezing, and flight and fight responses. In its rapid and imprecise form, the automatic, affective processing and reactivity to threatening interparental cues (e.g., hostility) would, in turn, organize constellations of responding that can vary widely along a continuum from no to full conscious awareness. Thus, the original unconscious, automatic affective response is increasingly supplemented by forms of reactivity that are under some cognitive control as the information processed by the amygdala and other neural pathways is transmitted to various regions of the cortex. Through this process, the initial automatic affective responses help to organize and direct attentional focusing and shifting of

Family History/Background 1. Interparental Conflict 2. Parenting Difficulties 3. Family-Level Processes 4. Child Characteristics

Proximal Interparental Conflict Characteristics 1. Anger 2. Aggression 3. Disengagement 4. Dysphoria

Automatic Affective Arousal and Reactivity

Internal Representations 1. Schemas 2. Expectancies 3. Attentional Focusing

Subjective Emotion and Impulses

Regulation of Overt Behavior and Emotion 1. Involvement/Avoidance 2. Dissembling Emotion 3. Hyperactive Emotion

Fig. 3. A process-oriented overview of the nature of the direct associations among characteristics of interparental conflict and multiple domains of children’s reactivity to conflict within an ethological and evolutionary perspective.

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conscious internal representations or appraisals (e.g., expectancies about the meaning conflict has for children), subjective experience of emotions, effortful strategies to regulate the overt displays of affect (e.g., amplifying or inhibiting emotion), and more sophisticated forms of regulating exposure to the interparental conflict (e.g., serving as a confidante or mediator). Bidirectional arrows between the response processes in Figure 3 further illustrate the transactional influences among the domains of responding that comprise the emotional security system. For example, patterns of attentional focusing and shifting to threat cues structured by the initial automatic affective response to the conflict may modulate subjective feelings of distress. Subjective distress, in turn, may further direct and sharpen vigilance to possible signs of interpersonal danger. However, in drawing again from analyses of the neural circuitry of the social defense system, we are not postulating that all the domains of responding in Figure 3 affect each other equally. Instead, as indicated by the solid arrow running from automatic affective arousal to the other responses, we propose that automatic affect initially organizes the responding of the other response domains and continues to modulate the nature and course of children’s reactivity to conflict for the duration of the event. Conversely, by virtue of its encapsulated nature, the reflexive affective reaction is relatively more resistant to alteration by the other response processes. Accordingly, the dotted arrow feeding back from the constellation of responses to the reflexive affective reaction indicates that the automatic affective reaction to the conflict runs its course with modest sway from the other response domains.

D. FAMILY ROOTS OF INDIVIDUAL DIFFERENCES IN PATTERNS OF SECURITY Figure 3 is also designed to illustrate how an appreciation of evolution and ethology advances an understanding of family sources of individual differences in relations among the response domains within the security system. Although natural selection likely equipped individuals with many ways of coping with threats in the family, dispositions to adopt a particular strategy are a complex function of both current ecological conditions and developmental histories, particularly in the context of interpersonal stress (Belsky, 2005; Ellis, Jackson, & Boyce, 2006; Gilbert, 2001). Translated to emotional security theory, the pathway between the proximal interparental conflict characteristics and children’s responses underscores the notion that a child’s response to parental discord depends in part on the nature of the parameters of the proximal conflict. In this manner, some degree of flexibility in tailoring responses to the specific challenges of the ongoing conflict is expected to emerge from the long histories of coping in the multiple niches within evolutionary environments. However,

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against this backdrop of lawful intraindividual plasticity and fluctuation, the arrow running from the characteristics of family history and background to the link between proximal characteristics of the interparental conflict and children’s patterns of responding illustrates our premise that stable patterns of security are likely to emerge from histories of experience within adverse family niches and trajectories of intrapersonal vulnerability (i.e., temperament). In the remainder of this section, we address how social defense strategies for achieving security (mobilizing-insecure, camouflaging-insecure, demobilizinginsecure, dominant-insecure, caregiving-insecure, secure) can be conceptualized as evolved regulatory schemes for coping with specific types of recurrent threats in the family and developmental risks (see Table II for details). However, at the outset, it is important to note that we are not proposing that prolonged exposure to specific family conditions will inevitably engender specific patterns of security in an absolute sense. Any specific dimension of interparental or family adversity can present varied and multiple challenges to children and are part of an open system in which other family and extrafamilial factors may alter the meaning of the specific adverse dimensions in the social defense system (Davies & Cicchetti, 2004; Keller & Nesse, 2006). Therefore, our formulation is geared toward identifying family and developmental cues that increase the probability that children will adopt a specific pattern of security. 1. Secure Pattern Secure children are hypothesized to have confidence in their parents in a way that maintains family harmony. Therefore, they exhibit little or mild distress in a form that is well regulated and expressed mainly in the form of empathy (Davies & Forman, 2002; Davies et al., 2006b). The underlying pattern of confidence of secure children is specifically theorized to evolve, in part, from witnessing wellmanaged parental disputes in the context of cohesive interparental and family relationships. Stable, supportive patterns of family and parent–child relationships may help to offset the negative impact of even occasional bouts of destructive interparental conflict on children’s concerns about security in two primary ways. First, children in supportive family systems are likely to develop expectancies that the family system is strong enough to weather the storm of intermittent interparental conflict without protracted relational damage (Davies et al., 2002). Second, parental abilities to dedicate resources to helping children process and understand their negative emotions and the stress of family adversity (e.g., emotion coaching) may also help to facilitate their coping and ability to efficiently preserve their security. Although research has yet to characterize the family histories of secure children, patterns of conflict reactivity fitting the secure profile are associated with higher levels of interparental harmony, parent–child attachment security, and family cohesion and lower levels of family adversity (Cummings & El-Sheikh, 1991; Davies & Forman, 2002; Maughan & Cicchetti, 2002).

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In evolutionary terminology, the predominance of family-level support suggests that the possibility of harm is negligible in the wake of any danger cues that accompany interparental discord in the homes of secure children. Thus, over time, the benign ecological niche likely requires few allostatic adjustments in the sensitivity of the defense system; the only likely change is lower levels of reactivity to subsequent threat to decrease unnecessary expenditure of resources (Nesse, 2005). In addition, temperamental characteristics reflecting advanced executive functioning (e.g., planning, inhibitory control, working memory, sootheability) and a high threshold for negative affect are theorized to be constitutional differences that bias the operation of the defense system toward developing a secure profile (e.g., Davies & Windle, 2001; Martin, Wisenbaker, & Huttunen, 1994). 2. Mobilizing and Camouflaging Patterns Reactivity patterns reflecting progressive increases in the sensitivity of the social defense system are theorized to develop in response to frequent danger in intraspecific ecological environments (Nesse, 2005). Within our reformulation of emotional security theory, children with mobilizing and camouflaging profiles of insecurity may share both an elevated sensitivity to interparental difficulties and a reliance on active defense strategies that reflect high arousal and fear. Accordingly, Table II shows that both profiles of insecurity are hypothesized to have many common etiological roots. In evolutionary models, the social defense system responds prepotently to conspecific anger and aggression (Hofmann et al., 2004; Ohman & Mineka, 2001). Accordingly the elevated distress, fear, and vigilance experienced by mobilizing and camouflaging children are postulated to reflect the hyperactivation of the defense system and result from repeatedly witnessing anger, aggression, and violence between their parents (Sloman et al., 2006). Likewise, common constitutional dispositions to experience negative affect, inhibition or shyness, and perceptual sensitivity in both groups of children may also further heighten the sensitivity of social defense system and concerns for preserving the goal of felt-security (Davies & Windle, 2001; Gilbert, 2001). However, if mobilizing and camouflaging are distinct patterns of insecurity in the interparental relationship, then these groups should differ in their developmental histories. The mobilizing strategy is likely to emerge from a history of contending with recurrent hostile threats without ample opportunity to disengage or escape. Within evolutionary models, these ecological niches produce intense, prolonged distress across multiple response domains (Sloman et al., 2006). By extension, we propose that mobilizing strategies are most often utilized when interpersonal and intrapersonal processes immerse children in the threatening interparental subsystem. At the interpersonal level (see Table II), family characteristics signifying enmeshed parent–child relationships (e.g., psychological control, resistant parent–child attachments), blurred boundaries between interparental and

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parent–child subsystems (e.g., child-related conflicts between parents, coparenting difficulties), and some degree of family cohesiveness (e.g., parental warmth) are conceptualized as further fueling children’s mobilizing strategies by emotionally pulling or coaxing them into interparental difficulties (Davies & Forman, 2002). At the intrapersonal level, constitutional dispositions reflecting difficulties regulating negative affect may also amplify mobilizing patterns. Supporting these hypotheses, preliminary findings indicated that children exhibiting high levels of distress and hypervigilance experienced multiple signs of family enmeshment, including elevated child-rearing disagreements, parental psychological control, and simultaneously elevated experiences of investment, worry, and disengagement in their families (Davies & Forman, 2002). In contrast, camouflaging strategies may be used in more dire ecological niches. Agonic conspecific relationships, which are defined by high levels of coercion and oppression by dominants, present a dilemma for organisms (Dixon, 1998). On the one hand, mounting fear, terror, and vigilance of victims of bullying by a dominant are likely to engender strong impulses to flee on the part of the subordinate. Yet, on the other hand, flight behaviors within these repressive environments are also likely to draw the attention and ire of the aggressive dominant. Thus, without the opportunity to escape, a primary solution is to remain within the social group but reduce salience as a target of aggression through freezing, inhibiting overt distress and escape behaviors, and maintaining safe distance from the dominant. Translated to our framework, “agonic” families bound together by rigidity, intimidation, and violence are particularly likely to engender a camouflaging strategy (Dixon, 1998). Table II specifically shows that high levels of domestic violence and volatility (e.g., interparental aggression, family instability), agonic parent–child interactions (e.g., parent–child aggression, disorganized attachment), and repressive socialization practices (e.g., intolerance of child emotional expression) are proposed to play a key role in the genesis and maintenance of a camouflaging strategy. Children exhibiting high levels of inhibitory control may be more likely to employ camouflaging by virtue of their relatively greater aptitude to suppress prepotent responses (i.e., distress) that violate the strict norms of the repressive family system. In support of our hypothesis, children from highly atypical and adverse family (e.g., violence) contexts are at greater risk for using camouflaging techniques characterized by dissembling or masking overt expressions of distress (Cole et al., 1994; Davies et al., 2006b; Shipman et al., 2000). However, empirical identification of the family and developmental correlates of a camouflaging pattern of insecurity awaits future research. 3. Demobilizing Pattern A demobilizing or “involuntary defeat” strategy is conceptualized in evolutionary models as a response of last resort and is thought to develop out of

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chronic arousal of the social defense system as individuals face challenges characterized by (a) lack of ecological resources and opportunities for escape from the threat, (b) inability to generate alternative solutions to escape the threat, and (c) high demand by others to comply (Dixon, 1998; Gilbert & Gilbert, 2003; Gilbert, 2004; Trower & Gilbert, 1989). Some of the properties of the ecological niches that lead to demobilizing strategies are postulated to be comparable to the origins of mobilizing and camouflaging strategies (e.g., lack of opportunities to withdraw or escape from threat; oppressive, coercive environment), but one difference is in the lack of any resources that might serve as a solace from threat (i.e., elements of condition “b” above). Applied to the interparental and family context in emotional security theory, this unique contextual factor may be manifested in critical, rejecting, cold, and indifferent family interactions that collectively belittle and disparage the child (Gilbert, 2001). Without any source of solace in the form of social support in the family, the “last resort” strategy of disengagement, anhedonia, dysphoria, and demobilization serves multiple functional roles of reducing the salience of the children (i.e., conspecific subordinate) in the face of possible threats by hostile, rejecting, and cold caregivers (i.e., aggressive dominant) and inhibiting motivation to explore and acquire resources in a competitive, threatening, and impoverished family context (Sloman et al., 2002, 2006). 4. Dominant Pattern The dominant strategy of conflict reactivity is characterized by high levels of behavioral distress, loss of control, dysregulation, and aggression in conjunction with low levels of subjective distress and appraisals of threat (e.g., Cummings, 1987; El-Sheikh et al., 1989). Children resorting to this strategy experience elevated levels of intense, poorly resolved interparental conflict, family disengagement, interparental dissatisfaction, parental dysphoria, avoidant parent–child attachment, and parental physical abuse and neglect (Cummings & El-Sheikh, 1991; Davies & Forman, 2002; Maughan & Cicchetti, 2002). Theory addressing how and why these family and developmental conditions breed dominant patterns remains undeveloped. However, Davies and Forman (2002) proposed that dominant (or, in their model, “dismissing”) patterns were particularly likely to be utilized by children when interparental conflict was part of a broader pattern of disengaged family relationships that promote, from the child’s perspective, a view of the family as a global source of stress rather than support. This conceptualization is supported by the elevated levels of disengagement, neglect, and dysphoria in interparental and family relationships seen in children with the dominant pattern. However, the profile of the family, at least on the surface, closely resembles the family configuration theorized to underlie the demobilizing pattern. Thus, exclusive reliance on the explanation by Davies and Forman (2002) does not disentangle the unique family or developmental conditions that distinguish dominant children from demobilizing children. Evolutionary theory

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may provide a promising base from which to develop a more refined and discriminating model of security. If children co-opt other systems or modules when the defense system does not protect against threats in the family, then a key task is to identify the sources of the perturbations in the defense system. One possibility is that temperamental difficulties characterized by impairments in inhibitory control, working memory, and perceptual sensitivity may conspire to undermine children’s ability to identify, process, and generate a coherent plan to cope with interparental conflict. Thus, elucidating constitutional and neuropsychological bases of dominant strategies is a central direction for future work (Gilbert, 2001). Another source of perturbations in defense-system function may be that the pernicious nature of interparental problems overwhelms the capacity of the social defense system. By extension, dominant children are likely to experience some of the same sources of family violence, rejection, and disengagement as demobilizing children. In fact, the blunting of subjective distress and threat is a hallmark of both insecure strategies and may reflect an “analgesic” response to pain under inescapable conditions of threat (Dixon, 1998; Gilbert, 2001; Gilbert & Allan, 1998; also see Davies & Forman, 2002). However, this still does not address the question of why, at a family level, the blunting of affect may become organized around a system of responding that is aggressive, domineering, and dysregulating. Guided by evolutionary theory, one possibility is that dominant patterns of responding are most likely to be enlisted when there are perturbations in the hierarchical structure of the social group. Collapses in the social structure of the group eliminate guidelines for access to resources and mean that individuals in the dominant role do not deter subordinates’ conduct violations (Sloman et al., 2006). Applied to our family process model, dispositions to utilize dominant strategies may be specifically amplified under conditions that reflect breakdown in the roles of parents as “dominants” in monitoring and managing their “subordinate” children’s conduct and activities (e.g., lax supervision and discipline; neglect). Another possibility derived from evolutionary theory is that dominant and demobilizing strategies simply reflect different stages in the developmental progression of adjusting to threatening ecological contexts. Models of social defense systems have consistently conceptualized a demobilizing profile as a strategy of “last resort” that temporally follows dominant patterns (e.g., Bowlby, 1969/1982; Dixon, 1998; Gilbert & Allan, 1998; Sloman et al., 2002). Accordingly, the primary locus of discrimination between dominant and demobilizing strategies may not lie as much in the emotional and hierarchical configuration of family relations as in the length of exposure to adversity. Although definitive tests of this hypothesis await longitudinal delineation of the developmental course demobilizing and dominant strategies, the consistent empirical documentation of aggressive behavioral patterns as developmental precursors of dysphoric and depressogenic functioning

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provides indirect support for the developmental progression hypothesis in evolutionary frameworks (Capaldi, 1992; Moffitt et al., 2002; Wiesner, Kim, & Capaldi, 2005). 5. Caregiving Pattern In ethological terminology, a caregiving pattern of insecurity in the interparental relationship reflects the use of “reverted escape” strategies within the social defense system that are further elaborated by the premature enlistment of the caregiving system (Gilbert, 2000; Hilburn-Cobb, 2004). Thus, the pattern is largely organized around a submissive approach to defending the self against harm, as parents in these family systems do not commonly abdicate their power to structure relationship processes (e.g., criticism) in a way that gives children little choice but to maintain their role as the primary caretaker of the family (Hilburn-Cobb, 2004). Thus, in addition to experiencing destructive properties of interparental conflict (e.g., hostility, aggression) that are similar in form to those experienced by other insecure children, children exhibiting an insecure profile may also be exposed to interparental problems that signify parental vulnerability and ineptness. Parental expressions of vulnerability (e.g., crying, fear) during or following interparental conflict are specifically theorized to be distinct risk factors in the development of a caregiving pattern because they highlight the dependent status of a family member (see Table I). Signs of parental weakness and defenselessness are postulated to be evident through active seeking of support from the child, parental psychopathology (e.g., alcoholism, substance use), and poor parental limit setting and guidance. Enmeshed, blurred boundaries within the family may further intensify patterns of caregiving by ensnaring children into the dysfunctional family unit and limiting opportunities to escape or disengage from the family (Gilbert, 2000). In support of our proposal, qualitative, clinical accounts of high-risk families indicate that children are at greater risk for assuming the role of emotional caretaker and confidante in the face of interparental difficulties when parents repeatedly express their overt fear, worry, and vulnerabilities, not only in the interparental subsystem (e.g., conflicts), but also through their reluctance and ultimate failure to assume the role of the dominant in the family (Byng-Hall, 2002; Wallerstein & Resnikoff, 1997). However, despite some research on the etiology of children’s general tendencies to exhibit role reversal in the parent–child subsystem (e.g., Chase, Deming, & Wells, 1998; Locke & Newcomb, 2004; MacFie et al., 1999; Macfie et al., 2005; Mayseless et al., 2004), empirical analyses of the family processes associated with the insecure pattern of caregiving in the interparental relationship have yet to be conducted. Toward this goal, future research would do well to explore multivariate models that also address the developmental and child characteristics. As illustrated in Table II, our main premise is that the probability of adopting an insecure caregiving pattern is likely a function of children’s exposure

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to repeated displays of vulnerability as well as intrapersonal attributes (e.g., working memory, inhibitory control) that endow children with the constitutional building blocks necessary to formulate complex, sophisticated strategies of intervening in complex adult problems.

IV. Emotional Insecurity and Children’s Developmental Trajectories Having outlined how an ethological perspective informs an understanding of the operation, origins, and correlates of children’s patterns of security in the interparental relationship, our final step is to address how behavioral systems may help elucidate the implications of children’s emotional security for their development and functioning. In this section, we first discuss why, at a broad level, prolonged activation of the defense system in response to chronic interparental discord may lead to children’s adjustment difficulties. In the remaining section, we illustrate how the identification of specific strategies of the social defense system (e.g., mobilizing, demobilizing) may afford a new level of precision in identifying individual differences in trajectories of specific forms of adjustment and maladjustment. A. GENERAL MECHANISMS OF EFFECT Although assessments of emotional insecurity in the interparental relationship have been shown to mediate partially children’s vulnerability to interparental discord (e.g., Cummings et al., 2006; Davies & Cummings, 1998; Davies et al., 2002), emotional security theory is in the preliminary stages of identifying why emotional insecurity in the interparental relationship is associated with children’s problems. To address this gap from an ethological perspective, we need to examine the process by which chronic activation of children’s defense systems in the context of interparental disputes may translate into children’s psychopathology. Activation of the defense system yields behavioral (e.g., escape, freezing), neurobiological (e.g., neuroendocrine reactivity), and cognitive (e.g., negative internal representations highlighting implications of threat cues) outputs that were exquisitely designed through natural selection to offer protection from harm (Marks & Nesse, 1994). The protracted operation of the social defense system is specifically theorized to set in motion multiple processes and pathways requiring considerable expenditure of biopsychological resources that ultimately increase children’s risky behavior and mental health problems. Accordingly, difficulties preserving felt-security in the interparental relationship are hypothesized to create deviations in the homeostatic balance and efficient psychobiological resource allocation that reverberate across multiple levels of functioning.

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Reflecting one class of putative pathways, children’s patterns of cognitive processing and interpreting of threats are proposed to vary as a function of their concerns about security in the interparental relationship and, in the process, affect how they appraise and interpret challenging contexts in the future. Distribution of threat within ecological niches over time was unlikely to be random across evolutionary history. Rather, threat (e.g., agonic conspecific relations) was likely to be relatively stable over the life course of our ancestors. Therefore, within evolutionary frameworks, cognitive scripts within the social defense module are theorized to serve an adaptive function of identifying, processing, and interpreting subtle or early cues of threat in the environment that afforded proactive utilization of action tendencies (e.g., avoidance) to reduce exposure to mounting threat (Hofmann et al., 2004; Ohman & Mineka, 2001). Applied to emotional security theory, recurrent threatening cues accompanying destructive interparental conflict are proposed to undermine children’s felt-security and specifically lead children to form negative internal representations of interparental relationship quality and their implications for the self and family. In turn, children are theorized to use these cognitive schemas as guides for interpreting and responding in other social settings. Dispositions to use these scripts may specifically be amplified in novel, stressful, or developmentally challenging (e.g., peer contexts in preschool; dating relationships in middle adolescence) contexts, as children simplify complex stimuli by checking new settings for old dangers. At another level of analysis, prolonged concerns about security and its accompanying operation of the defense system may also undermine development by altering the functioning of neurobiological processes within the limbic–hypothalamic– pituitary–adrenocrotical (LHPA) axis, sympathetic–adrenomedullary system, and neurotransmitter functioning (Gilbert, 2001; Repetti, Taylor, & Seeman, 2002). For example, the LHPA axis and one of its hormonal products (i.e., cortisol) are components of the neuroendocrine system that may play a key role in shaping the developmental sequelae of children’s insecurity in the family. Cortisol is a hormone produced from the reciprocal interplay among components of the LHPA axis in response to environmental stress. In contexts of threat, the LHPA axis marshals physical and psychological resources through allocation of resources to biological systems (Lopez, Vazquez, & Olson, 2004). Healthy functioning consists of the efficient onset and termination of the LHPA system tailored to meet the demands of the context without significantly disrupting homeostatic functions. However, exposure to family and interparental discord is theorized to disrupt progressively the operation of the LHPA system; the resulting wear and tear harms children’s mental and physical health (e.g., Cicchetti & Rogosch, 2001; Davies, Sturge-Apple, Cicchetti, & Cummings (in press); Granger et al., 1998). However, a broader analysis of multiple psychobiological processes is necessary to understand accurately the implications of defense system activation for the development of psychopathology.

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A third interlocking component of the mediational process linking defense system activation and development of adjustment difficulties and psychopathology is reflected in impairments in children’s neuropsychological and psychological mechanisms necessary to regulate emotion and behavior effectively in the face of developmental and social challenges. Attention focusing and shifting, task persistence, response inhibition, problem-solving, and organization of effective responses to challenge require particularly large reservoirs of biopsychological resources. Consequently, prolonged expenditure of energy accompanying protracted concerns about security may be particularly likely to disrupt these dimensions of functioning (Fearon & Belsky, 2004). The collective perturbations in these domains of functioning may, in turn, be manifested in emotion dysregulation, impulsivity, and risk-taking behaviors that underlie the development of several forms of psychopathology, including both internalizing and externalizing problems (e.g., Posner et al., 2003; also see Davies et al., 2006b).

B. SPECIFICITY IN THE SEQUELAE OF PATTERNS OF SECURITY We believe that experiences of specific forms of psychopathology and adjustment difficulties hinge partially on individual differences in how children’s emotional insecurity is expressed and the explanatory mechanisms involved in the development of psychopathology. Specifically, our ethologically informed reformulation of emotional security theory generates predictions about which organizational patterns of defense activation in the service of security are precursors to different forms of psychological adjustment. The patterns of security are specifically regarded as response processes that, as a general rule, evidence moderate consistency across time within the specific relational context of the interparental subsystem. Moderate stability also reflects that dynamic change is possible, with discontinuity commonly regarded as a lawful product of changes in family circumstances experienced by children. However, plasticity and change in the defense system become progressively more limited as children continue along a given development course of security (Cicchetti & Cohen, 1995; Cummings, Davies, & Campbell, 2000; Waddington, 1957). Thus, despite the ongoing potential for change, increasing tendencies to respond in specific ways to interparental conflict are theorized to serve as useful guides for interpreting and responding to new, challenging interpersonal contexts and, in the process, crystallize into forms of maladjustment that persist across time and settings (Davies & Cummings, 2006). To advance our tentative system for characterizing different response patterns further, we briefly address how each of the six patterns of insecurity in the interparental relationship may inform an understanding of child developmental psychopathology.

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1. Mobilizing Pattern Extended bouts of heightened vigilance, proneness to distress, physiological arousal, and primed negative appraisals experienced by mobilizing-insecure children closely correspond to the defining features of anxiety and social withdrawal difficulties. According to evolutionary conceptualizations, acute awareness to potential interpersonal threat, preoccupation with the analysis of the impact of the one’s own behavior on social contexts, and submissive, appeasing (e.g., coy) behaviors are evolved mobilizing strategies for reducing harm in the face of conspecific threat (Gilbert, 2001; Wakefield, 1999). Yet, the cost of the progressive intensification and proliferation under highly stressful family circumstances is the oversensitivity of the defense system and resulting difficulties with social anxiety and withdrawal (Gilbert, 2001; Marks & Nesse, 1994). Consequently, relatively stable mobilizing patterns are proposed to be most strongly and consistently linked with the development of internalizing difficulties such as generalized anxiety, social anxiety, and social withdrawal symptomatology. Depressive and dysthymic symptoms are also postulated to be relatively common sequelae of the mobilizing pattern. However, within our model, the depressogenic process is posited to be mediated by the role of demobilizing patterns of insecurity. As we discussed in Section IIID, demobilizing patterns are theorized to evolve from mobilizing patterns of insecurity under unmanageable conditions such as chronic exposure to destructive interparental conflict and comorbid forms of family adversity (Sloman et al., 2002, 2006). Thus, consistent with this indirect pathway, we expect that the mobilizing pattern will be a consistent, but relatively weaker, predictor of depressive symptoms than anxiety and social withdrawal difficulties. 2. Camouflaging Pattern Dispositions of camouflaging children to suppress behavioral outputs of distress, escape, or defensive hostility in the face of conspecific threat are viewed through the lens of ethology as enclosed avoidance strategies that reflect underlying impairments in approach mechanisms (Chance & Jolly, 1970; Gilbert, 2001). In contrast to the blocked escape strategies comprising the demobilizing pattern, enclosed avoidance does not involve attempts to withdraw or disengage from the social context. Rather, enclosed avoidance is reflected in high arousal and vigilance that are thought to take a considerable toll on the neurobiological functioning of the individual. Supporting this prediction, Spangler and Grossman (1993) reported that infants with avoidant attachment, who are conceptualized as employing strategies of enclosed avoidance in the parent–child relationship (exhibiting low overt distress), evidenced elevated heart rate and cortisol levels during separations and reunions. The stress of maintaining a high state of arousal coupled with dampened behavioral reactivity can be pathogenic and is hypothesized

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to lead to social withdrawal and defensive avoidance of social signals and interpersonal disengagement. Empirical work has also suggested linkages between social distancing and avoidance as a defensive strategy in response to interpersonal conflict and the occurrence of depressive symptomatology (Allan & Gilbert, 1997). 3. Demobilizing Pattern Demobilizing patterns are likely to hold the adaptive function of providing a mechanism for inhibiting challenges for resources following repeated social defeats in highly threatening settings. In the context of interparental conflict, the old remnants of this system may be manifested in several response domains. Behavioral outputs of disengagement and inhibition of exploratory behavior are proposed to have the adaptive function of signifying to conspecifics the low threat value of demobilizing individuals (Gilbert, 2006; Sloman et al., 1994). Helplessness, dysphoria, anhedonia, and lassitude resulting from exposure to interparental discord serve to exacerbate and maintain the behavioral signs of demobilization (Gilbert & Allan, 1998). Given their striking resemblance to the diagnostic criteria for depression and dysthymia, characteristics of a demobilizing pattern of insecurity in the interparental relationship are particularly likely to intensify into broader constellations of mood disorders. Important questions, however, remain about how this pattern increases vulnerability to depressive symptoms. For example, the social rank model suggests that representations of the self as socially trapped, defeated, and in an unwanted subordinate position are the primary mechanisms mediating the development of mood difficulties (e.g., Gilbert, 2001; Gilbert et al., 2002; Sloman et al., 2002). Alternatively, the situation–symptom congruence hypothesis suggests that the mechanisms mediating associations between demobilization in the interparental relationship and the development of depression may depend on the fit between the child’s specific response pattern and the interpersonal context (Keller & Nesse, 2006). Sadness, dysphoria, and pining for social support may be operative depressogenic mechanisms within some family circumstances (e.g., social loss), whereas fatigue, rumination, and learned helplessness may spawn depression in other family situations (e.g., goal failure). The situation– symptom congruence hypothesis raises the further question of whether specific strategies comprising a “demobilizing” pattern of responding may each have their own adaptive function that promoted ancestral fitness within different contexts. Although dysphoria and disengagement are conceptualized in the social rank model as holding the adaptive function of reducing harm by “laying low” and signaling submissiveness to conspecifics (Gilbert, 2006; Sloman et al., 1994), other strategies comprising the demobilizing pattern may have increased ancestral fitness in other contexts by increasing energy conservation or soliciting social support (Keller & Nesse, 2006; Sheeber et al., 1998).

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Our prediction that a demobilizing strategy is a particularly strong predictor of mood disorders should not be misinterpreted to suggest that it should be unrelated to other psychopathology. According to social rank theory, because longterm demobilization strategies are employed in response to recurrent threat, high levels of arousal, vigilance, and worry are not uncommon experiences (Sloman et al., 2002). Thus, demobilizing strategies may also confer greater vulnerability to anxiety symptoms. 4. Dominant Pattern Dominant-insecure children’s attempts to suppress the experience of vigilance, distress, and fear by enlisting the service of the dominant system is theorized to result in a wide range of mental health difficulties, particularly externalizing forms of maladjustment. Coping by blunting subjective distress involves defensively downplaying the value of close family relationships. Reliance on the dominance system serves to breed further children’s ill regard for the family unit and as a training ground for elaborating and refining aggressive patterns of responding. For example, enlisting the dominance system may be a useful method for seizing attention and control in the context of perturbations in the interparental (Emery, 1989) or the parent–child attachment relationship (Greenberg et al., 1997). Over time, hostile views of the social world, growing social disenfranchisement, callousness, and the rigid, reflexive use of a wide repertoire of aggressive behaviors in new social settings (e.g., peer settings) are likely to coalesce into broader patterns of conduct problems, delinquency, and antisocial symptomatology (Davies & Forman, 2002). Evocative reactions by peers and adults in school settings may further intensify children’s aggressogenic patterns and likely limit their selection of peer affiliations to antisocial networks. Anxiety and distress that are organizational cornerstones of the dominant-insecure pattern may also promote, to a less robust degree, internalizing symptoms such as social withdrawal, anxiety, or, ultimately, depressive symptoms in the face of recurrent social rejection (e.g., Capaldi, 1992; Moffitt et al., 2002; Wiesner et al., 2005). 5. Caregiving Pattern Many characteristics of the caregiving-insecure pattern—including involvement, role reversal, and parentification—are thought to engender a short-term benefit of upholding some degree of stability and predictability in a family replete with vulnerable and inept adults. Nevertheless, recurrent employment of the strategy is likely to carry several long-term pathological consequences. At a broad level, forms of parentification (e.g., as acting as a confidante, peacekeeper, protector) reflect considerable emotional investment, forethought, and preoccupation with adult problems. These are likely to inhibit the development of skills and allocation of resources necessary to approach other important developmental

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tasks, thereby resulting in failure to resolve successfully stage-salient tasks and developmental trajectories of broad psychological incompetence (e.g., Davies, 2002; Macfie et al., 2005). By sacrificing their own developmental needs in favor of their parents’ welfare, children may have particular difficulty with stagesalient tasks of autonomy, individuation, and identity development (Chase, 1999; Fullinwinder-Bush & Jacobvitz, 1993). Impairments in identifying and pursuing goals and the repeated failure to manage entrenched adult troubles successfully are also theorized to engender high levels of anxiety, mood, and self-disorders (Byng-Hall, 2002; Jacobvitz & Bush, 1996; Wells & Jones, 2000). However, forms of parentification are not always consistently associated with children’s adjustment problems (e.g., Byng-Hall, 2002; Jacobvitz & Bush, 1996; Jurkovic, 1997; Mayseless et al., 2004). For example, Tesak (2005) found that children’s parentified involvement in interparental conflict did not significantly predict parent or teacher reports of child internalizing and externalizing symptoms 1 year later. This work highlights the broader value of identifying the intrapersonal and family attributes that may serve as sources of heterogeneity in the modest, inconsistent pathways between parentification and child psychological problems (i.e., Path 4b in Figure 1). The risk posed by caregiving patterns to children’s development may vary as a function of the pattern and organization of the insecure-caregiving pattern in the family. For example, spousification— in which the child is called upon by the parents to serve the role of the partner in fulfilling their intimate needs—is theorized to be particularly damaging to children, setting the stage for a wide range of psychological difficulties, including inattentive, overactive, and impulsive symptoms consistent with attention and defiant problems (e.g., Carlson, Jacobvitz, & Sroufe, 1995; Jacobvitz & Sroufe, 1987; Kasius et al., 1997; Macfie et al., 2005). In contrast, insecure caregiving manifested in other forms or settings (e.g., when parents acknowledge and value children’s caretaking efforts) may have a benign impact on the mental health of children (e.g., Jacobvitz & Bush, 1996; Mayesless et al., 2004). At the level of child characteristics, high levels of working memory, inhibitory control, and perceptual sensitivity are proposed precursors of the caregiving-insecure pattern (see Table II); yet, they may actually serve to buffer or protect many caregiving-insecure children from any psychological damage associated with parentification. 6. Secure Pattern Confidence in the parents to manage their own disputes effectively in a way that preserves or improves family confidence is a defining feature of the secure pattern that guarantees that concerns about felt-security and the operation of the defense system become salient only under the most threatening and dire of family circumstances (Davies & Forman, 2002). Therefore, the relatively high activation threshold and efficient preservation of the defense system likely promote psychological and physical health by permitting the efficient distribution of

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biopsychosocial resources to stage salient tasks (e.g., close friendship formation during childhood) and shielding the integrity of biological systems against wear and tear caused by the corrosive effects of stress (e.g., LHPA system; Gilbert, 2001; Repetti et al., 2002). Likewise, as part of the profile of security, positive representations and patterns of responding are likely to promote a wider array of coping and problem-solving strategies that serve as prototypes for adaptability to novel and challenging social tasks (Thompson & Calkins, 1996). Accordingly, representations of secure children are not characterized simply by the absence of constricting, negative representations for progressively limiting coping patterns and resulting opportunities to resolve interpersonal challenges (Johnston & Roseby, 1997). Rather, within evolutionary theory, positive affect and representations underlying secure patterns are postulated to facilitate flexibility in adjusting to novelty and stress in interpersonal contexts by permitting children to safely explore and experiment with variations in response patterns that are increasingly tailored to the specific characteristics of the task or environment (Gilbert, 1993).

V. Conclusion In closing, novel theoretical contributions in advancing and refining emotional security theory have been progressively waning since its inception. To advance both the precision and the scope of emotional security theory, the main theme of our chapter was to introduce a reformulation of emotional security theory cast within an ethological framework. Prior accounts of emotional security theory regarded evolutionary assumptions and concepts as unnecessary theoretical baggage. In contrast, our overarching aim here has been to address how an ethological framework provides some conceptual direction in addressing four major unaddressed questions in the theory including: (1) How and why is emotional insecurity in the interparental relationship similar to, but distinct from, attachment security in its form and function? (2) Can different patterns of insecurity in the interparental relationship be lawfully deciphered based on the organization of children’s responding to interparental conflict? (3) How and why are specific forms of interparental conflict and broader configurations of family functioning associated with various ways of responding to conflict and profiles of security? (4) Can we achieve greater precision in delineating the multiple pathways and mechanisms in associations between differences in children’s organization of responding to conflict and their trajectories of mental health and illness? Many of our assumptions and predictions are speculative in this early stage of theoretical development, but our incorporation here of an ethological perspective in emotional security theory has generated significant gains in theoretical leverage, power, and precision. Therefore, we view an ethological perspective as an

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indispensable catalyst rather than useless deterrent in future conceptual refinement and empirical testing of the emotional security theory.

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PROCESSING LIMITATIONS AND THE GRAMMATICAL PROFILE OF CHILDREN WITH SPECIFIC LANGUAGE IMPAIRMENT

Laurence B. Leonard DEPARTMENT OF SPEECH, LANGUAGE, AND HEARING SCIENCES PURDUE UNIVERSITY, WEST LAFAYETTE, IN 47907, USA

I. II.

INTRODUCTION PROFILES OF SLI ACROSS LANGUAGES A. ENGLISH B. GERMAN, DUTCH, AND SWEDISH C. ITALIAN AND SPANISH D. THE CHALLENGE OF CROSSLINGUISTIC DIFFERENCES

III.

ALTERNATIVE ACCOUNTS OF SLI

IV.

PROCESSING LIMITATIONS IN SLI A. ACCOUNTING FOR THE BROADER LANGUAGE DEFICIT B. EXTRAORDINARY DIFFICULTY WITH GRAMMATICAL MORPHEMES C. PROCESSING LIMITATIONS AND CORRELATED PATTERNS IN THE SLI GRAMMATICAL PROFILE D. CAN PROCESSING LIMITATIONS ACCOMMODATE THE SLI PROFILE SEEN IN OTHER LANGUAGES? E. EXPLAINING DIFFERENCES IN DEGREE OF USE

V.

IMPLICATIONS

VI. CONCLUSIONS ACKNOWLEDGMENTS REFERENCES

I. Introduction The term “specific language impairment” (SLI) applies to children who exhibit a significant deficit in language ability that cannot be attributed to disruptions or delays in other areas of functioning. Children with SLI pass screenings of hearing acuity, they show no signs of neurological damage, they score within normal limits on tests of nonverbal intelligence, and they do not display the symptoms characteristic of autism. Epidemiological studies suggest that the prevalence of SLI may be as high as 7% among 5-year-olds (Tomblin et al., 1997).

139 Advances in Child Development and Behavior R.V. Kail : Editor

Copyright © 2007 Elsevier Inc. All rights reserved.

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For many children with SLI, the disorder appears to have a genetic basis (SLI Consortium, 2002). However, genetic sources are likely to be multifactorial (Bishop, 2002). Certain genetic loci associated with SLI are also associated with motor development; others are associated with risk for autism. A combination of genetic sources may well lead to the condition regarded as SLI. Children with SLI have the most conspicuous symptoms during the preschool years when they show marked weaknesses in their sentence structure and somewhat milder limitations in vocabulary and phonological skills. Although these children improve significantly as they progress through the preschool and early elementary school years, problems remain for many children (e.g., Bishop & Adams, 1990; Tomblin, Freese, & Records, 1992). Subtle problems in oral language persist and reading disabilities are common. Indeed, research suggests that SLI and developmental dyslexia are comorbid developmental language disorders (Catts et al., 2005). The language impairment seen in children with SLI is not uniform; different areas within language tend to be more adversely affected than other areas. For many children, the area of morphosyntax is most seriously impaired. This area includes the use of grammatical morphemes (e.g., the inflections -s and -ed in runs and jumped and functions words such as is and are) and syntactic structure (e.g., as expressed in the distinction between Who was pushing the girl? and Who was the girl pushing?). Among children with SLI acquiring English, tense and agreement seem to be especially weak; productions such as Everyday mommy drive to work, Yesterday daddy play golf, and Gina watching TV often persist into school age. In contrast, vocabulary skills, although below age level, are not as weak as morphosyntactic skills in these children. Furthermore, these children’s pragmatic ability—that is, their use of language in a social context—can be considered a relative strength, though, of course, pragmatic details requiring the greatest morphosyntactic sophistication (e.g., indirect requests such as Could you please hand me the pencil?) represent obstacles for these children. Given the uneven profile of language abilities seen in SLI, theories of this disorder must not only provide a suitable explanation for the general weakness in language but also the more serious deficit in the area of morphosyntax. In this chapter, I review the details of the SLI profile in English and several other languages and discuss how alternative theories of SLI account for this profile. I emphasize processing accounts of SLI. Although the evidence supporting the general feasibility of such accounts abounds in the SLI literature, attempts to explain how processing factors can produce the uneven profile characteristic of SLI have been rather limited. Using a variety of sources, I attempt to show how a general processing limitation might result in the kind of profile seen in SLI and how the details of this profile can be expected to change depending on the language being learned.

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II. Profiles of SLI across Languages The task of explaining the uneven language profile observed in SLI might be less challenging if the same uneven profile were seen in all languages. However, this is decidedly not the case. The dominant profile varies according to language family (e.g., Germanic, Romance), and even within language families there are certain reliable crosslinguistic differences. These differences suggest that any universal factor underlying the areas of extraordinary weakness in SLI cannot boil down to difficulty with notions such as tense or agreement, at least without considering how these notions are expressed in a particular language. Rather, it seems that any universal factor responsible for these special problems must interact with language-specific characteristics to produce the uneven profile associated with each particular language. To identify potential sources of difficulty, then, it is important to examine language profiles across languages. In this section, I review evidence from those languages for which there are sufficient data to identify a dominant profile with confidence.

A. ENGLISH By far the greatest amount of research on SLI has focused on English-speaking children. The “telegraphic” look of young typically developing children acquiring English is especially pronounced in children with SLI. That is, whereas typically developing children produce their first two- and three-word sentences with relatively few function words and grammatical inflections (e.g., Daddy make popcorn; There Mommy car), for children with SLI, the sparse use of function words and inflections continues even when they begin to produce utterances of sufficient length to support these grammatical details. Evidence for this exaggerated telegraphic pattern is especially clear in studies that employ a research design in which children with SLI are compared to both typically developing same-age peers and younger typically developing children matched according to mean length of utterance (MLU). In studies of this type, English-speaking children with SLI are less consistent than both same-age peers and younger MLU control children in their use of grammatical morphemes such as third person singular -s, past tense -ed, auxiliary is and are, among others (e.g., Johnston & Kamhi, 1984; Leonard et al., 1997; Oetting & Horohov, 1997; Rice & Wexler, 1996). Given that children with SLI produce utterances of the same length as those used by MLU control children in these studies, they might be expected to be as proficient as the younger control children in their use of grammatical morphemes. Yet, the group differences clearly indicate that this is not the case. Differences in grammatical morpheme use between children with SLI and MLU control children take the form of differences in percentage of use in

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obligatory contexts. Despite their clear difficulties, almost all children with SLI show some degree of use of these morphemes. However, at an age when these morphemes should be used consistently in contexts that require them, children with SLI may use them in only 30–80% of such contexts. With one notable exception, when grammatical morphemes are produced by children with SLI, they are almost always in appropriate contexts. For example, children with SLI may produce either The dogs are over here or The dogs over here, but productions such as The dogs am over here are extremely rare. The only exception is the production of “overregularizations” of past, as in She throwed the ball. Note that the strong tendency to limit grammatical morphemes to appropriate contexts suggests that the children’s inconsistent use cannot be construed as haphazard use, for children seem to know when not to use these morphemes. Furthermore, their use of forms such as throwed indicates that their use of -ed is rule-based and not simply memorized. It can be seen, then, that any account of the less frequent use of these morphemes by children with SLI must also provide a means of explaining some degree of grammatical knowledge on the children’s part. Some researchers have reported a correlation between the inclusion or omission of tense/agreement morphemes and the accuracy of the pronouns used in subject position. Specifically, an inappropriate pronoun form is more likely to occur when the tense/agreement morpheme is omitted than when it appears (e.g., Loeb & Leonard, 1991; Wexler, Schütze, & Rice, 1998). Thus, Her running and Him take a bath everyday are common, but Her’s running and Him takes a bath everyday are not. In contrast, productions such as She’s running often co-occur with productions such as She running. Accounting for this distribution pattern has been one of the challenges that face theories of SLI. Adults do not produce sentences such as Him take a bath everyday, and even if children simply selected the wrong pronoun, it is not obvious why a tense/agreement morpheme should be less likely when an incorrect pronoun is used than when the appropriate pronoun is produced. Grammatical morphemes and subject pronouns are not the only areas of morphosyntax that are problematic for English-speaking children with SLI. These children are more likely than same-age peers to omit obligatory arguments (e.g., saying The boy put the glass or The boy put on the table in place of The boy put the glass on the table) and more likely than both same-age peers and younger vocabulary-matched children to exclude optional arguments (e.g., describing a situation as The boy rolled the ball rather than The boy rolled the ball under the porch) (Fletcher, 1991; Fletcher & Garman, 1988; Ingham et al., 1998; Johnston & Kamhi, 1984). In addition, they show less diversity of argument structures with the same verb. For example, children with SLI may produce She’s loading the bricks onto the truck but not She’s loading the truck with bricks or vice versa (Loeb et al., 1998; Thordardottir & Ellis Weismer, 2002). For verbs such as load,

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the endpoint of an action can be expressed either as the object of a preposition (onto the truck, in the first example) or as the direct object (the truck, in the second example). No single argument appears to be consistently problematic for children with SLI; instead, the problem seems to be one of inconsistency in using arguments and limited argument structure diversity with particular verbs. Finally, when presented with a novel verb in a sentence (e.g., The car zafs the train to the truck) without benefit of visual information, children with SLI have more difficulty than younger controls in acting out a plausible interpretation for the sentence (van der Lely, 1994). Complex sentences—those with more than one lexical verb, as in She wanted him to go and I think he washed the car—are used at a later age and used less frequently by children with SLI than by their age controls (Eisenberg, 2003; Schuele & Dykes, 2005). However, even greater difficulty is seen in the details of the children’s productions. Nonfinite complement clauses (that is, complement clauses not requiring markers for tense or agreement) are more likely to show omissions of to (e.g., She wanted him go) and finite complement clauses often have missing tense and agreement morphemes (e.g., I think he wash the car) or missing arguments (e.g., I think washed the car) (Owen & Leonard, 2006). One element of morphosyntax that poses less difficulty for English-speaking children with SLI is word order. Attempts at active, declarative sentences almost always reflect the appropriate order of words. Errors seem to be confined to sentences that do not conform to the typical agent/subject–verb–patient/object order of English sentences. Passives are often difficult for these children, as are wh-questions in which the agent is not the subject (e.g., Who was the funny little girl chasing?) (Deevy & Leonard, 2004; van der Lely, 1996).

B. GERMAN, DUTCH, AND SWEDISH Since the 1990s, considerable research has been devoted to children with SLI acquiring Germanic languages such German, Dutch, and Swedish. Like their English-speaking counterparts, these children have more difficulty than younger MLU-matched peers in their use of tense and agreement morphology (e.g., Bartke, 1994; de Jong, 1999; Hansson, Nettelbladt, & Leonard, 2000; Rice, Noll, & Grimm, 1997). However, the percentages of use of these morphemes in obligatory contexts are considerably higher than in English (Leonard et al., 2005; Roberts & Leonard, 1997). The appearance of the errors on tense and agreement morphology also differs from that of errors in English, at least on initial inspection. Whereas English-speaking children produce bare stems in place of present and past tense inflected forms (e.g., play in place of plays and played), children acquiring languages such as German, Dutch, and Swedish are more likely to produce a verb form with an overt infinitive inflection in place of present and

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past tense inflected forms (e.g., in Swedish, lek-a “to play” in place of lek-er “plays” and lek-te “played”). (As we shall see later, some scholars think this difference between English and other Germanic languages is only superficial, as the English infinitive is a bare stem.) Although word order errors in English are rare, they are quite common in the speech of children with SLI acquiring German, Dutch, and Swedish (e.g., Hansson et al., 2000). A reason for this crosslinguistic difference is that, unlike English, these other Germanic languages have a “verb-second” rule. For sentences with the subject in initial position, word order resembles that of English (e.g., in German, Die Frau fand die Kinder, “The woman found the children”). However, if an element other than the subject begins the sentence, the verb, not the subject must appear in second position (e.g., Gestern fand die Frau die Kinder, “Yesterday found the woman the children”). Such nonsubject-initial sentences are used to place emphasis on certain elements of the sentence or for other discourse reasons. Some children with SLI attempt such sentences but incorrectly retain the subject-verb order seen in subject-initial sentences (thus producing ungrammatical versions such as Gestern die Frau fand die Kinder). Another type of word order error is sometimes seen in German and Dutch, though not in Swedish. When children with SLI fail to use a tense/agreement inflection and instead produce an infinitive, they often place the infinitive at the end of the sentence, as in the German example Jenny das kochen, “Jenny that (to) cook.” In the adult grammar of German and Dutch, the infinitive does appear in sentence-final position when tense/agreement is expressed on an auxiliary verb that appears in second position (e.g., Jenny kann das kochen, “Jenny can that cook”). A related error is seen when a participle form rather than an infinitive is produced in sentence-final position, as in Jenny das gegessen, “Jenny that eaten.” In German, the present perfect is often used to express past events, and when this construction is used properly, with an auxiliary verb, the participle does occupy final position, as in Jenny hat das gegessen, “Jenny has that eaten.” I return to a discussion of these word order errors in a subsequent section of the chapter.

C. ITALIAN AND SPANISH Children with SLI acquiring Romance languages such as Italian and Spanish show a pattern of use that differs dramatically from English and other Germanic languages. Several tense/agreement inflections are used as proficiently by these children as by same-age peers, and few differences are seen between SLI and MLU-matched comparison groups (e.g., Bedore & Leonard, 2001, 2005; Bortolini, Caselli, & Leonard, 1997). Percentages of inflection use in obligatory contexts are significantly higher than is seen for English-speaking children with SLI (Bortolini, Leonard, & Caselli, 1998). In one sense this is a paradox. Inflections

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are very difficult for children with SLI in English, and one might expect even more serious difficulty for children learning Italian and Spanish, languages in which inflections abound. Yet, Italian- and Spanish-speaking children with SLI are far more skilled in their use of inflections than are English-speaking children with SLI. Function words tend to be more problematic for children with SLI acquiring Italian and Spanish. These include articles, certain auxiliary verbs, and direct object clitics (Bedore & Leonard, 2001; Bortolini & Leonard, 1996; Leonard & Bortolini, 1998; Restrepo & Gutierrez-Clellan, 2001). Direct object clitics are pronoun-like forms that are used when the referent representing the direct object is clear from the physical or linguistic context. They are unlike direct object pronouns in English because they cannot stand alone (e.g., they cannot serve as a one-word answer to a question such as “Who broke the window?”) and they occupy a position before the verb rather than after the verb, unlike their noun counterparts. Thus, whereas “I see Paula” in Italian is (io) vedo Paula, the sentence “I see her” is (io) la vedo, with the direct object clitic la preceding, rather than following the verb. In both Italian and Spanish, omissions of these function words constitute the most frequent error made by children with SLI, though substitutions also occur, especially in Spanish. As more research is conducted on languages such as Italian and Spanish, additional problems will likely be uncovered in the speech of children with SLI acquiring these languages. For example, the MLUs of these children are well below age level, and omissions of obligatory arguments and sentence elements necessary for complex sentences probably contribute to this reduced sentence length. In contrast, the available evidence suggests that word order is not an area of difficulty for Italian- and Spanish-speaking children with SLI. These languages have more flexible word order than English but, unlike the “verb-second” Germanic languages, the use of an element other than the subject in sentenceinitial position does not require an obligatory positioning of the remaining elements. For example, each of the sentences prendo io il caffe (“Take I the coffee”), il caffe prendo io (“The coffee take I”), and il caffe io prendo (“The coffee I take”) can be appropriate, depending on the speaking context.

D. THE CHALLENGE OF CROSSLINGUISTIC DIFFERENCES Any plausible account of SLI must not only provide a reason for the inconsistent use of morphosyntactic details by children with SLI but also explain why the problematic details are not the same from language to language. Children with SLI acquiring English are extremely telegraphic in their speech—and show special weaknesses in the use of tense/agreement morphology—yet show little or no difficulty with word order. Children with SLI acquiring German, Dutch,

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and Swedish exhibit moderate levels of difficulty with tense/agreement morphology, yet are considerably more proficient than their English-speaking counterparts. However, these same children are relatively poor in their ability to meet the word order requirements of their language. Children with SLI acquiring Italian and Spanish stand out from children with SLI acquiring English and other Germanic languages in their relatively consistent use of appropriate tense/agreement morphemes, especially verb inflections.

III. Alternative Accounts of SLI Several proposals designed to account for the profile seen in SLI have been grounded in current linguistic theory (e.g., Clahsen, 1989; Rice & Wexler, 1996; van der Lely, 1998; Wexler, 1998, 2003). Although these accounts differ in important details, they share the assumption that SLI is a deficit in linguistic knowledge. That is, it is assumed that children with SLI have incomplete knowledge of particular rules, principles, or constraints that are operative in typical language development. Some of these accounts hold considerable promise (see, e.g., the application of Wexler’s 1998 account in Bedore & Leonard, 2005, and Leonard et al., 2005). However, accounts of this type have yet to overcome two obstacles. First, although they correctly acknowledge that children with SLI have at least some minimal ability to use the morphosyntactic details that give them so much trouble, such accounts characterize this minimal use as the output of a grammar that treats these details as “optional.” That is, morphosyntactic details that are obligatory in the adult system (e.g., past tense -ed) are presumably treated as merely optional in the grammars of children with SLI. The difficulty with this optionality construct is that there are reliable and replicable differences between children with SLI and younger typically developing children in degree of use of these morphosyntactic details even when both groups fall well below 100% use of these forms (see Leonard & Deevy, 2006). For example, Rice, Wexler, and Cleave (1995) found significant differences between children with SLI and younger MLU-matched controls in the use of third person singular -s, past tense -ed, and auxiliary/copula be forms, with means of 30 vs 45%, 23 vs 53%, and 45 vs 65%, respectively. Furthermore, there are reliable differences in degree of use between, for example, English-speaking children with SLI and Swedish-speaking children with SLI, even when both groups are within the “optional” period of development. For example, Leonard et al. (2005) found mean percentages of past tense inflection use of 53% for English and 86% for Swedish, even though the children with SLI in the two language groups were carefully matched for both age and severity of impairment relative to normative data. In short, there appear to be meaningful differences in

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degree of use that are not captured by the simple optional use—obligatory use dichotomy. If children are either in an optional stage or in an (adult-like) obligatory stage of use, it should not be possible to find predictable and reliable differences in degree of use between two groups when both groups’ use places them in an optional stage. A second obstacle facing accounts based on linguistic theory is that they usually focus on a significant area of difficulty in morphosyntax but do not address the fact that children with SLI also have milder though detectable deficits in a wider range of language areas. For example, although Englishspeaking children with SLI have serious difficulties with tense/agreement morphology, they are less consistent than typically developing children in their use of argument structures and are below age level in their vocabulary skills. Therefore, even if the linguistic theories provide a correct account of particular difficulties in morphosyntax, these theories are incomplete in ignoring deficits in other areas of language; consequently, different theories must be proposed to explain these other deficits. Such a position should be adopted only when more parsimonious attempts at explaining the full range of symptoms of SLI prove unsuccessful.

IV. Processing Limitations in SLI Since the 1980s, there has been evidence that children with SLI have problems with language that go beyond their knowledge of words and morphosyntactic details. As a group, they also perform below age level on “processing” tasks, that is, on tasks that emphasize the amount of material to be integrated and stored and the time available for completing these operations, even when such tasks involve materials that have minimal linguistic content (e.g., Ellis Weismer & Hesketh, 1996; Evans, 1996; Gillam, Cowan, & Marler, 1998; Johnston, 1994; Marton & Schwartz, 2003; Montgomery, 2000a, 2000b). The literature on processing limitations in children with SLI permits two general conclusions. First, problems are seen on both speeded tasks, in which response time is the critical measure, and tasks of working memory, in which the amount of material recalled is the important metric. Children with SLI have been found to respond more slowly than same-age typically developing peers on tasks ranging from picture naming, to judging whether two words rhyme, to judging whether a sentence is grammatical (e.g., Lahey & Edwards, 1996; Miller et al., 2001). Working memory tasks showing deficits in children with SLI include word-recall tasks (e.g., Kirchner & Klatsky, 1985) and, especially, tasks of phonological working memory in which children must repeat nonwords of varying lengths (Dollaghan & Campbell, 1998; Ellis Weismer et al., 2000; Gathercole & Baddeley, 1990; Kamhi et al., 1988; Montgomery, 1995).

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The second general conclusion is that speed of processing limitations and limitations in working memory are not limited to the verbal domain. For example, Johnston and Ellis Weismer (1983) found that children with SLI are relatively slow on nonlinguistic mental rotation tasks, in which they have to judge whether two geometric figures (one rotated by varying degrees) are the same. In fact, as first discovered by Kail (1994), children with SLI seem to be slower than sameage peers by approximately the same proportion across a wide range of tasks, nonlinguistic as well as linguistic. His findings have received support from subsequent studies by Windsor and Hwang (1999) and Miller et al. (2001, 2006). Windsor et al. (2001) have noted that alternative analysis procedures may reveal different degrees of slowing across subdomains. However, the breadth of the processing speed limitations of children with SLI seems rather clear. Some investigators have found that the significant verbal working memory deficits of children with SLI can be accompanied by deficits in visual–spatial working memory (e.g., Bavin et al., 2005; Hoffman & Gillam, 2004), though this finding is not universal (see Archibald & Gathercole, 2006).

A. ACCOUNTING FOR THE BROADER LANGUAGE DEFICIT One of the advantages of a processing limitation perspective on SLI is that this type of account offers a means of handling a wide range of language weaknesses. The studies on phonological working memory provide a plausible explanation for the vocabulary limitations seen in children with SLI. Specifically, if children cannot retain phonological sequences long enough to form adequate phonological representations, multiple encounters with each new word will be needed before it is established in the lexicon. As a result, vocabulary learning should be slow (Baddeley, Gathercole, & Papagno, 1998). A slow rate of vocabulary learning can also adversely affect morphosyntax. This is especially true in the case of verbs. Children must have considerable familiarity with a verb to learn its argument structure. For example, sufficient encounters with the verb break would be necessary to learn that the object broken can appear in subject position in nonpassive sentences (e.g., The bottle broke) as well in postverb position (e.g., He broke the bottle). Similarly, for a verb such as give, the recipient can follow the verb directly (She gave Chris some money) or appear in a prepositional phrase following the direct object (She gave some money to Chris). As noted earlier, children with SLI seem to be restricted in the diversity of their argument structures. The formation of complex sentences can similarly be delayed by a protracted period of verb learning. Children must learn which verbs take sentence complements (e.g., Jill knows that Paul can’t drive) as well as simple direct objects (e.g., Jill knows Paul) and the kind of sentence complements they can

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take. For example, some verbs take only nonfinite clauses (e.g., Gina wanted Rex to leave), others take only finite clauses (e.g., Gina thought Rex arrived at six o’clock), and still others take both types (e.g., Gina hoped to pay the bill; Gina hoped that Rex paid the bill). Even when verbs and their argument structures are learned, processing limitations can cause problems in the comprehension and production of morphosyntax. For example, Montgomery (1995) compared children with SLI and a group of younger typically developing children on their comprehension of short and long sentences with the same syntactic structure (e.g., The little boy climbs the tree; The dirty little boy climbs the great big tall tree). The children with SLI performed less accurately than the comparison group on the longer versions of the sentences, even though the additional words in these sentences did not provide crucial cues to sentence interpretation (e.g., a dirty boy was not contrasted with a clean boy). Montgomery interpreted his findings as indicating that the processing capacity limitations of the children with SLI interfered with their ability to understand syntactic structures that were otherwise well within their capability. Another example is seen in the work of O’Hara and Johnston (1997). Following earlier findings by van der Lely (1994) that children with SLI have difficulty interpreting sentences containing novel verbs, O’Hara and Johnston administered a similar task and carefully analyzed children’s errors. Children heard sentences such as The doctor fets the monkey to the lion and were encouraged to select appropriate toys from a larger set and act out the sentence in a manner that reflected its possible meaning. Children with SLI performed less accurately than a group of younger typically developing children. However, an analysis of their errors suggested that the source of the problem was related more to processing ability than to knowledge of the structure of the sentences. For example, the children with SLI erred more often on sentences with three arguments (as in The doctor fets the monkey to the lion) than with two arguments (as in The lion dokes the monkey). In addition, noun errors showed recency effects (the first and second nouns were more likely to be omitted or substituted than the final noun), and substitution errors were within class (a doctor character was replaced by a man and a cow was replaced by a bear, but a doctor was not replaced by a bear, and so on). Errors rarely reflected a lack of understanding of the syntactic relations of the sentence. Deevy and Leonard (2004) also reported evidence in line with the view that processing factors affect morphosyntactic comprehension. Previous work (e.g., van der Lely & Battel, 2003) had shown that children with SLI have much greater difficulty with sentences that presumably require grammatical movement than those that do not. For example, for the wh-question Who was pushing the zebra? it is possible to interpret the utterance as a simple subject–verb–object sentence and arrive at the correct response by simply replacing who with the name of the

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subject (Who was pushing the zebra? The boy was pushing the zebra.). This is not true for a question such as Who was the zebra pushing? (Who was the zebra pushing? The zebra was pushing the boy.). A linguistic interpretation of this difficulty is that children with SLI fail to grasp that elements ordinarily occupying one position in the sentence (postverb position in this case) can occupy the sentence-initial position in a question without changing their semantic role. Deevy and Leonard reasoned that questions such as Who was pushing the zebra? and Who was the zebra pushing? also differ in their processing demands because the latter requires the child to hold in memory the wh-word for a longer stretch of the sentence before coming to its interpretive position, as can be seen from a comparison between 1(a) and 1(b): 1. (a) (b) (c) (d)

Who [x was pushing the zebra]? Who was [the zebra pushing x]? Who [x was pushing the big strong zebra]? Who was [the big strong zebra pushing x]?

To determine whether greater distance and hence greater demand on working memory was a more plausible explanation than knowledge of grammatical movement, Deevy and Leonard (2004) added two additional sentence conditions, illustrated in 1(c) and 1(d). Both 1(c) and 1(d) contain more words than their counterparts in 1(a) and 1(b). However, whereas the wh-question shown in 1(c) did not require the children to hold the wh-word in memory for a greater distance than its counterpart in 1(a), the wh-question in 1(d) placed the greatest demand on the children, even though it did not differ from 1(b) in terms of whether grammatical movement was involved. The findings were consistent with a processing interpretation. Relative to a group of younger typically developing children, children with SLI had disproportionate difficulty with questions of the type shown in 1(d). From a processing perspective, this type of question placed the greatest demands on working memory. Examples of errors in production that might be attributed to processing demands can also be found in the literature. Grela and Leonard (2000) tested children with SLI and younger MLU control children who were inconsistent in their use of auxiliary are. Children were presented with scenarios involving toys and props and were asked to describe these scenarios in sentences. The sentences most appropriate for the scenarios differed in the number of arguments required. Based on current sentence production models (e.g., Bock & Levelt, 1994), Grela and Leonard assumed that when generating a sentence, each argument that must be retrieved requires processing resources; hence, sentences involving more arguments will test the limits of the processing capacity of children with SLI. When capacity limits are approached, fragile areas of the children’s morphosyntactic system, such as the auxiliary are, will

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be vulnerable to omission. Of course, “fragile” must be defined by independent means. In this case, auxiliary are can be defined as fragile on an a priori basis because the development of tense/agreement morphemes such as are lags behind the development of most other details of language in children with SLI even when processing demands are minimal. The most frequent problem with such morphemes is omission; hence when production is rendered more difficult due to processing demands, omission is the most likely type of error. The findings confirmed the expectations of Grela and Leonard (2000); children with SLI used auxiliary are less frequently than did the younger typically developing children. In addition, children with SLI were more likely to omit the auxiliary are when the sentence required three arguments (as in The ducks are giving the blocks to the mouse) than when it required only two (as in The pigs are pushing the bus) even when sentence length was controlled. Leonard et al. (2000) also looked at consistency in using auxiliary forms as a function of processing demands. These investigators made use of a syntactic priming paradigm (e.g., Bock & Loebell, 1990). Children described pictures requiring auxiliary is (e.g., The fox is chasing the dog). These target pictures were preceded by prime pictures and sentences (presented by the experimenter and repeated by the child) that either matched the target sentences in syntactic structure (e.g., The cats are drinking the milk) or required a syntactic structure very different from that of the target sentences (e.g., The dog barked). The assumption was that the production of prime sentences with syntactic structure identical to the structure needed for the target would increase the likelihood that the children would include the auxiliary form in their target sentence production. That is, by virtue of having been produced in the preceding prime, the appropriate syntactic structure had been activated and thus should be more readily retrieved for the target. This facilitated retrieval, in turn, should permit more resources to remain for the retrieval of the function words of the sentence, including auxiliary is (note that the facilitating prime The cats are drinking the milk shared syntactic structure with the target, but employed a different auxiliary form, are). Leonard et al. (2000) found that children with SLI made less use of auxiliary is in the target sentence productions than did a group of younger typically developing MLU-matched children. In addition, the SLI group showed significantly larger priming effects than the comparison group. This finding was taken to reflect a greater vulnerability to processing demands on the part of the children with SLI. In summary, accounts that assume processing limitations offer a means of explaining a wide range of language deficits seen in SLI, including difficulties in comprehension as well as production. Problems in areas ranging from vocabulary to argument structure to complex sentences to grammatical morphology seem amenable to these types of accounts.

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B. EXTRAORDINARY DIFFICULTY WITH GRAMMATICAL MORPHEMES The examples in the preceding section illustrate potential processing effects on grammatical morpheme use (auxiliary forms in this case), but do not explain why these forms should be especially fragile in the speech of children with SLI. There have been several preliminary attempts to account for this type of extraordinary difficulty (Bishop, 1994; Fletcher, 1992; Leonard, 1989). Leonard et al. (1997) proposed that children with SLI have speed of processing limitations that are especially hazardous for grammatical morphemes of brief duration. These are grammatical morphemes in the form of word-final consonants (e.g., -ed) and nonfinal weak syllables that appear in contexts in which they cannot be significantly lengthened (e.g., is in sentence-initial and sentence-medial position). These investigators assumed that children with SLI are capable of perceiving such morphemes, but have difficulties completing all of the operations necessary for processing these morphemes given their brief duration. That is, children must not only detect the morphemes, but also discover their grammatical function and place them in the proper cell of a morphological paradigm. Paradigms are subsystems of grammatically related inflections or function words. They contain cells formed by a conjunction of levels of different dimensions. For example, the English paradigm for copula forms of be contains cells representing the conjunction of tense (to distinguish, e.g., is from was), number (to distinguish is from are), and person (to distinguish is from am); the paradigm for tense/agreement inflections contains cells representing tense (to distinguish, e.g., jumps from jumped) and, within present tense, the conjunction of person and number (to distinguish I jump from she jumps from they jump). Languages differ in the subsystems that constitute paradigms (e.g., some languages do not employ copula verbs) and the dimensions that are operative in these paradigms (e.g., in some languages copula forms differ by tense only, not by number or person). Therefore, children must build these paradigms on the basis of the evidence provided in the language input. The operations involved in paradigm building—detecting a morpheme, hypothesizing its potential grammatical function, and provisionally placing it in a cell of a paradigm—must occur in real time, while the remainder of the utterance is being heard. The demands of performing these operations when a morpheme is brief will often result in incomplete processing of the morpheme. As a result, a greater number of encounters with the morpheme will be necessary before it is established in the child’s grammar. There are several ways in which an encounter with a brief grammatical morpheme can result in incomplete processing. First, the morpheme (either a function word or an inflection) might decay from working memory completely and be lost before morphological analysis has been completed. Second, inflected words (e.g., jumped, plays) might decay partially and then be mistaken as the

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bare stem form of the same word (e.g., jump, play) due to the similarity between the two. Third, morphological analysis of a function word might not occur because processing was still focused on preceding material when the function word appeared in the sentence. Fourth, processing of an inflected word might be abandoned prior to the inflection in favor of the next word appearing in the sentence. Each of these cases of incomplete processing represents the functional equivalent of reductions in input frequency. That is, because the incompletely processed morpheme is lost, it plays no role in paradigm building. Therefore, a greater number of encounters will be needed for a sufficient number to be fully processed and contribute to the paradigm. The importance of a morpheme’s duration should be apparent, given the assumptions made by Leonard et al. (1997). Specifically, brief morphemes must be detected and analyzed quickly, because there is little time before new material in the sentence will appear. In addition, if analysis is focused on preceding material in the sentence, brief morphemes that immediately follow this material may be missed altogether by the time processing can be directed toward them. A review of the SLI findings (see Leonard, 1998) provides general support for the view that brief grammatical morphemes are especially difficult for children with SLI, in line with this general account. (Later I note some possible exceptions.) For example, the English grammatical morphemes that mark tense and agreement are relatively brief and constitute areas of extraordinary difficulty for these children. In a series of studies, Montgomery and Leonard (1998, 2006) showed that children with SLI are less sensitive to brief grammatical morphemes than grammatical morphemes with greater duration. These investigators used a word-monitoring task in which the word to be identified was preceded either by a grammatical sequence of words or by a grammatical error (e.g., Tyler & Cobb, 1987). Typically, response times are slower in responding to the target word when it is preceded by a grammatical error than when it is preceded by fully grammatical material. This difference is taken to reflect awareness that the error is in some way out of place. Montgomery and Leonard created errors by omitting grammatical morphemes that, when produced, are relatively brief (present third person singular -s) or relatively long (progressive -ing). They found that children with SLI in fact responded more slowly to target words that were preceded by grammatical errors, but only when the omitted morpheme was relatively long. Thus, on average, response times were slower for items such as 2(a) than for items such as 2(b) (the target word appears in italics): 2. (a) Jessie found John at the lunch table. John was mad and was pour soup all over the floor. (b) Sam’s school is raising money for a trip. This Saturday morning they were washing cars and mowing grass.

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In contrast, these children showed no response time differences when the omitted morpheme, when produced, was brief. Thus differences in response time were not observed for items such as 3(a) and 3(b): 3. (a) Jeff usually makes a big supper. Most evenings he cook meat and potatoes and lots of vegetables. (b) John’s mom is a great baker. Most nights she bakes cookies for him and the whole family. In contrast, a group of typically developing children matched for age and a group of younger typically developing children showed response time differences for brief-duration morphemes as well as for morphemes of greater duration. Some grammatical morphemes are similar or identical in their phonetic characteristics, yet they are not identical in the degree of difficulty they pose for children with SLI. The most obvious example is -s as a noun plural versus -s as a present tense third person singular verb inflection. For noun plural -s, the evidence is somewhat mixed, with some authors reporting group differences between children with SLI and MLU controls and others not (see Leonard, 1998). However, the findings are very clear in showing that the differences between SLI and MLU-matched groups are larger for present third person singular -s than noun plural -s. Because -s can be viewed as a relatively brief grammatical morpheme, it might be assumed that these findings argue against the proposals advanced here. However, on close inspection, this assumption seems premature. The durations of these two types of -s inflections are not the same. Hsieh, Leonard, and Swanson (1999) recorded stories read by a group of mothers to their young (typically developing) children. They then analyzed the duration of all noun plural -s and third person singular -s inflections produced by the mothers. On average, the durations of noun plural -s were 40% longer than the durations of third person singular -s. This overall difference is largely a function of sentence context. Nouns—and thus also noun plural forms—frequently occur in sentencefinal position (e.g., Here are the plates; These are nice trucks; I want some grapes). Fricatives are significantly lengthened in this position. In contrast, third person singular -s occurs in sentence-final position in only a handful of sentence constructions (e.g., I know what she wants). It is also the case, as Hsieh et al. document, that words with noun plural -s inflections are much more frequent in English usage than words with third person singular -s inflections. These findings suggest that children hear more instances of noun plural -s than instances of third person singular -s, and a larger proportion of these noun plural -s examples are longer in duration than the examples of third person singular -s. Considering the assumptions about more encounters needed to overcome incomplete processing, and the importance of duration, these facts are likely to accentuate the differences in the acquisition rate of these two grammatical morphemes.

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Although duration seems to play an important role, especially in SLI, it would be quite naïve to argue that this factor alone, or in combination with frequency of occurrence, can fully account for differences in the acquisition order of grammatical morphemes. Factors such as semantic transparency and the regularity of the morphological paradigm are among those that contribute to the ease with which children acquire grammatical morphemes (e.g., Leonard, 1989; Slobin, 1985). Leonard et al. (1997) assumed that factors such as these will influence the acquisition order of grammatical morphemes by children with SLI in the same way they influence acquisition order in typically developing children. However, in the case of SLI, the acquisition gap between any two morphemes may be greater than usual if the later-acquired morpheme is brief in duration or narrower than usual if the earlier-acquired morpheme has brief duration. It is also noteworthy that the grammatical morpheme differences discussed thus far can be shown as well in studies in which normally functioning adults or children must respond to sentences presented under difficult conditions, such as when the auditory input is degraded (Kilborn, 1991) or when the participant must perform a second operation, thus necessitating the sharing of cognitive resources (e.g., Blackwell & Bates, 1995). Hayiou-Thomas, Bishop, and Plunkett (2004) demonstrated the same type of effect using typically developing 6-year-old children and a grammaticality judgment task. For example, when recorded sentences were speeded up by compressing them to 50% of their original rate, children’s accuracy on sentences with past tense and third person singular inflections was adversely affected to a greater extent than on sentences with noun plural inflections. Similarly, sentences with past tense and third person singular inflections were considerably more difficult for the children when they contained additional, superfluous material than when the sentences lacked such redundant material (e.g., Last week my very clever father fixed a nasty dent in his shiny car versus Last week my father fixed a dent in his car). This performance difference between longer and shorter sentences was much smaller for sentences containing noun plural inflections. It would appear, then, that the morphemes that are most difficult for children with SLI are also the most vulnerable in typically developing children when processing demands are increased significantly. Such a finding increases the plausibility that processing limitations in children with SLI may play an important part in these children’s great difficulty with particular grammatical morphemes. Of course, it can be argued that these findings apply only to day-to-day functioning after the individuals have already acquired the morphemes, not to the actual acquisition process. However, similar differences between morphemes have also been found in computer learning simulations. Hoeffner and McClelland (1993) employed a three-layer architecture involving a semantic layer, a hidden layer, and a phonological layer. To simulate problems that children with SLI might have with brief morphemes, these investigators weakened

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the phonological input to the system and hypothesized that past tense -ed and third person singular -s would be learned with greater difficulty than progressive -ing given the phonological differences—and especially the duration differences— among these morphemes. These investigators also included irregular past items, with the goal of determining whether, despite the hypothesized difficulty in learning -ed, the system would produce occasional overregularizations (e.g., throwed), as have been observed in the speech of children with SLI. The predictions of Hoeffner and McClelland (1993) were borne out. Weakening of the phonological input did not appreciably affect performance on -ing relative to a model in which phonological input was undisturbed. However, performance on both -ed and -s was clearly reduced in the SLI model. Despite the reduced performance on -ed, overregularizations occurred. Similar findings were reported by Marchman (1993) in a computer simulation study devoted exclusively to past tense forms. These findings are important in showing that when the input cannot be processed fully, brief morphemes are more vulnerable than those with greater phonetic substance, but are nevertheless registered to a sufficient extent to be applied in creative ways. Joanisse and Seidenberg (1998, 2003) extended the work of Hoeffner and McClelland (1993) by showing that reductions in phonological input can have select, negative consequences on pronoun resolution, as in the different referents for him and himself in sentences such as Bob thinks that Stan likes him/himself. Even with reduced phonological input, the distinction between him and himself should be detectable. However, Joanisse and Seidenberg argued that the imprecise phonological information that was provided was sufficient to tax the model’s ability to perform an adequate syntactic analysis of the sentences. They likened this finding to the extra demands that reduced phonological input might place on the working memory of children with SLI. They also noted that when semantic cues were available to supplement syntactic analysis, the model performed at much higher levels. For example, performance on Bob thinks that Sally likes him proved to be relatively high. These studies are instructive in demonstrating how processing factors can have specific, rather than global, effects on children’s morphosyntax.

C. PROCESSING LIMITATIONS AND CORRELATED PATTERNS IN THE SLI GRAMMATICAL PROFILE Earlier, I noted that English-speaking children with SLI show variability in their use of tense/agreement morphemes; He’s running, for example, might well co-occur with He running in the same speech sample obtained from a child with SLI. However, I also mentioned that productions such as Him running sometimes occur, yet those such as Him’s running are quite rare. How can processing limitations explain such a pattern?

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Certainly, it can be demonstrated that appropriate subject pronouns such as he are very brief in duration (e.g., Read & Schreiber, 1982) and therefore problematic for children with SLI given the processing limitations assumed here. However, the pattern in question is one of replacing subject pronouns with incorrect forms, not omitting them altogether. One must be able to explain the appearance of him in subject position. From one processing limitation perspective, this pattern is quite counterintuitive. Specifically, if processing demands are high, certain trade-offs might be expected; the child would either omit the auxiliary (He running) or use the wrong pronoun (Him’s running). In fact, the most frequently reported data suggest that when children use the incorrect form of the pronoun, the auxiliary is even less likely to be used than if the appropriate pronoun form is produced. Yet there may be a processing-based explanation for this pattern. Tomasello (2003) accurately pointed out that children hear clauses such as him running in longer sentences, as in I saw him running and Did you see him running? Errors such as Him running are seen in the speech of young typically developing children for a brief period of time. Such errors remain for much longer periods in the speech of children with SLI. If these children are faced with working memory limitations, they might hear sentences such as Did you see him running? and retain the final nonfinite clause (him running) without its link to the preceding portion of the sentence. In the literature on SLI, many kinds of sentences are documented in which missing auxiliary forms, copula forms, and inflections are accompanied by inappropriate pronouns in subject position. Close inspection reveals that most of these can be found as nonfinite clauses in longer (fully grammatical) adult utterances, as in 4: 4. (a) (b) (c) (d) (e) (f)

Me do the dishes My coffee hot Her at home Him running Him jump Them fly away

Will you watch [me do the dishes] I like [my coffee hot] I want [her at home] I saw [him running] Let’s watch [him jump] Did you see [them fly away]

It can be seen, then, that if working memory limitations steer children with SLI toward the retention and processing of sentence-final clauses, they may come to regard clauses such as Her at home and Them fly away as grammatically acceptable. Earlier I pointed out that utterances such as She running, He jump, and She at home are also found in the speech of children with SLI. If working memory limitations are severe, such utterances might derive from adult utterances of the type Is [she running]? Will [he jump]? Was [she at home]?

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Freundenthal, Pine, and Gobet (2006) used a computational model that explicitly attempted to create an output that included nonfinite utterances such as He jump along with finite utterances (as in He jumps) that are known to co-occur with the nonfinite forms in the speech of young typically developing children. Of course, co-occurring utterances such as He jump and He jumps are also used by children with SLI, for a protracted period of time. Utterances comparable to Him jump were not examined in this investigation. The model that Freundenthal et al. (2006) created had an utterance-final processing bias such that elements at the end of the sentence had a disproportionate influence on the sentences the model created based on the input. Note that this bias is in line with an assumption of working memory limitations in children with SLI, with recency effects operating in the form of better retention of sentence-final information. With increasing learning, the model generated utterances of increasing length. Freundenthal et al. employed child-directed speech samples as input to the model. The output provided a good approximation of the variable use of inflections by young children. One important detail in this success was the appearance of child-directed utterances of the type Can he go? As pointed out earlier, such utterances have a nonfinite verb in final position and an appropriate subject pronoun immediately preceding it. In the early stages of the model’s learning, utterances such as He go are thus reflecting the input in combination with the utterance-final processing bias. Gradually, as longer utterances are generated, forms such as Can he go begin to appear.

D. CAN PROCESSING LIMITATIONS ACCOMMODATE THE SLI PROFILE SEEN IN OTHER LANGUAGES? English-speaking children with SLI show lower percentages of use of tense/agreement morphemes than children with SLI learning other Germanic languages, as well as children learning Romance languages such as Italian and Spanish. At least two processing-related factors might contribute to these crosslinguistic differences. First, a much larger proportion of English tense/agreement morphemes are brief in duration, expressed through word-final stop and fricative consonants or nonfinal weak syllables. Word-final syllables represent a larger proportion of tense/agreement morphemes in these other languages. Second, English makes much greater use of bare stems—words that carry no inflection—not only for the infinitive but also for “zero-marked” finite forms such as first person singular (e.g., I run), third person plural (e.g., They run), and so on. Other Germanic languages are much more restricted in their use of bare stems, and Italian and Spanish do not use them at all. These two factors of brief duration and bare stem frequency conspire to render processing more difficult for English-speaking

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children with SLI, as brief duration morphemes are less likely to be fully processed given the speed of processing limitations assumed in SLI, and the ubiquity of bare stems in English could easily lead the child to regard incompletely processed inflected words as bare stems. The word order errors seen in languages such as German, Dutch, and Swedish can also be related to processing limitations. The most common error of this type is seen when the children fail to place the verb in the second position when an element other than the subject begins the sentence. In such cases, they often produce the subject in the second position with the verb appearing next, as in the ungrammatical production in Swedish, Sen Kristina dricker kaffe, “Then Kristina drinks coffee,” instead of the correct version, Sen dricker Kristina kaffe, “Then drinks Kristina coffee.” Although non-subject-initial utterances are relatively common, subject-initial sentences with subject–verb–object order are most frequent and are considered to reflect the canonical word order of these languages. Faced with processing limitations, children with SLI acquiring these languages might retain the subject–verb–object order as a default while they focus on the grammatical morphology. A common error seen in German-speaking children with SLI is the use of an infinitive or participle in sentence-final position, in contexts that seem to require use of a finite verb marking tense/agreement in second position. Examples of such errors are Oliver Kaffee trinken, “Oliver coffee (to) drink,” and Jan Paula gesehen, “Jan Paula seen.” From the standpoint of English, at least, these errors seem unusual because the verb is both marked inappropriately (nonfinite infinitive or participle inflection) and placed inappropriately (sentence-final rather than sentence-second position). However, in longer adult utterances, these sequences do, in fact, appear, as in Kann [Oliver Kaffee trinken]? “Can Oliver coffee (to) drink?” and Hat [Jan Paula gesehen]? “Has Jan Paula seen?” These examples parallel the English examples such as Can [he go]? discussed earlier, though reflecting the German placement of infinitives that are used with modal verbs (such as kann “can”) and participles that are used with auxiliary forms (such as hat “has”). If children’s working memories are restricted, these sentence-final portions of sentences might well be retained and then treated as acceptable main clauses. This interpretation gains support when we consider Swedish, a verb-second language like German. Productions of infinitives in finite contexts occur in the speech of Swedish-speaking children with SLI, but these infinitives are not placed in sentence-final position as they are in German. However, as in our examples from English and German, the errors nevertheless match the final portions of adult utterances. For example, an error such as Kristina dricka kaffe, “Kristina (to) drink coffee,” bears a striking resemblance to adult productions such as Kan [Kristina dricka kaffe]? “Can Kristina (to) drink coffee?” In each of these languages, then, errors that seem quite unique to the language share the

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common feature of being potentially related to longer utterances produced by adults. If working memory limitations lead children with SLI to retain final portions of utterances, these kinds of utterances might be expected. Finally, it can be noted that in a language such as Italian, infinitive and participle forms are rarely seen as replacements for verbs requiring tense/agreement inflections in the speech of children with SLI. There are probably two reasons for this. First, Italian is a null-subject language such that when the subject is clear from the linguistic or nonlinguistic context, it is not expressed. Thus, utterances of the form Può nuotare? “Can (he/she) swim?” are very frequent in the input. Second, when a subject is used, it very rarely appears between the modal verb and the infinitive or the auxiliary verb and the participle. An Italian equivalent of “Can Gina drink coffee?” is likely to be Può bere caffè Gina? “Can drink coffee Gina?” Similarly, the equivalent of “Has Gina seen the film?” is likely to be Ha visto il film Gina? “Has seen the film Gina?” Note that this order in the adult’s input to the child does not contain a portion with a subject–infinitive or subject–participle sequence equivalent to the English Gretchen ride a bike (from Can [Gretchen ride a bike]?); to the German Oliver Kaffee trinken, “Oliver coffee (to) drink” (from Kann [Oliver Kaffee trinken]? “Can Oliver coffee (to) drink?”); or to the Swedish Kristina dricka kaffe, “Kristina (to) drink coffee” (from Kan [Kristina dricka kaffe]? “Can Kristina (to) drink coffee?”). These errors from German, Swedish, and Italian differ from each other and from those seen in English. Yet, they share the property of being smaller segments of longer utterances that can be traced to the input of the respective language. Thus, although the errors look different, they can be generated by the same factor—a limitation in working memory that restricts the scope of linguistic material that can be fully processed.

E. EXPLAINING DIFFERENCES IN DEGREE OF USE Although I have described some plausible processing-related reasons for expecting particular morphosyntactic difficulties, patterns of use across morphemes, and crosslinguistic differences, I have postponed until now the important question of differences in degree of use. Earlier I mentioned that children with SLI and younger typically developing children matched on a measure such as MLU differ reliably in their degree of use of particular grammatical morphemes even though neither group has attained mastery levels. Percentage differences of 25% versus 45% or 50% versus 80% are commonly reported. Although such differences are not adequately captured by notions such as “optionality,” processing-based accounts seem to provide a means of explaining

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them. For illustration, consider Pinker’s (1984) proposals for building morphological paradigms. According to Pinker, children initially form word-specific paradigms by detecting presumably related forms (e.g., want–wants), hypothesizing the grammatical function served by the inflection, and placing it in a paradigm. Single dimensions (e.g., singular) are hypothesized first; only when the evidence in the input contradicts the single-dimension hypotheses will the child hypothesize the conjunction of two dimensions (e.g., singular and present tense). The conjunction of three dimensions (e.g., singular and present tense and third person) will be hypothesized if the two-dimension solution is incompatible with the evidence in the input. The cells in the paradigm are not created or split until a form potentially reflecting a new dimension is detected and hypothesized. For example, a child’s paradigm for the verb push will not be divided according to tense until the form pushed is encountered and hypothesized to reflect past tense. After a number of word-specific paradigms have been developed, the common material in the same cell across word-specific paradigms is entered into general paradigms. These general paradigms then apply to partially filled word-specific paradigms to fill out the remaining cells. For example, assume that a child’s wordspecific paradigms for jump, walk, and several other verbs contain entries for present third person singular (e.g., jumps, walks). The child might then form a general paradigm with the shared material (free of the stem), -s, entered in the cell for present third person singular. If the child then encounters a new verb such as flip, the child might be able to generate flips in a present third person singular context by applying the inflection in the corresponding cell of the general paradigm. Paradigms are not formed instantaneously but must be built up gradually. With each successful act of detecting the morpheme in a context that supports its hypothesized grammatical function, the morpheme’s placement in the paradigm cell is strengthened. However, there are false starts and some morphemes lose their place in a paradigm in favor of other morphemes. For example, the hypothesis that wants serves (only) a singular function is disconfirmed upon detection of I want and you want; similarly, the hypothesis that it serves (only) a third person function must be rejected upon detection of they want. However, even when the correct hypothesis is formed, the entry of wants into a present third person singular cell of the paradigm is not a simple matter. Note that the many instances of bare stems in the input have also prompted the child to hypothesize that want can represent present tense (because the child has heard I want, you want, we want, they want in present tense contexts) or singular (given that I want and you want have been heard in singular contexts). Thus, forms compete, and the proper cell divisions and entries within each cell evolve only after many encounters with the exemplars in the input. Until an entry is consolidated in its proper cell, the competition between forms leads to inconsistent use, with selection of the appropriate form increasing in proportion to its relative strength in the paradigm.

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Given these assumptions, consider how speed of processing limitations may render the paradigm building process more difficult and, consequently, prolong the period of inconsistent use by children with SLI. As noted earlier, instances of incomplete processing amount to reductions in input. Yet the insertion and strengthening of a morpheme in a paradigm depends on successful encounters with the morpheme in the input, that is, instances in which the morpheme is not only detected but retained long enough to be tested against the hypothesized grammatical function. Children with speed of processing limitations are therefore likely to have entries in paradigms that are weaker and still in competition with bare stems. In fact, the appropriate morpheme will be in an even weaker position if, as in one of my assumed scenarios, the inflected form (e.g., jumps) decays and is mistaken for the bare stem (e.g., jump); in this case, the bare stem, not the appropriate inflected form, might be registered as a candidate for the grammatical function hypothesized. This possibility might extend the period during which the appropriate morpheme is used only intermittently. The grammatical morpheme problems discussed previously can be attributed to the interaction of speed of processing limitations, morpheme duration, and paradigm building. Some aspects of grammatical morpheme difficulties can also be discussed in terms of processing capacity. According to Pinker (1984), the greater the number of dimensions reflected in a morpheme, the greater the number of dimensions that must be considered simultaneously, which, in turn, places greater demands on processing capacity. Morphemes reflecting present tense only place fewer demands on the learner than those reflecting the conjunction of present tense and singular, and so on. Dromi et al. (1999) tested this notion in a study of Hebrew-speaking children with SLI, their typically developing same-age peers, and a group of younger typically developing children matched for MLU. Hebrew is a language with a rich morphology that permits null subjects (in past tense) and, in key respects, produces data that are not unlike those seen for a language such as Italian. Specifically, for many tense/agreement inflections, children with SLI show percentages of use that do not differ from those shown by MLU controls. The Hebrew verb paradigm is quite uneven. Within present tense, inflections reflect the conjunction of tense, number, and gender; however, within past tense, inflections can reflect either the conjunction of tense, person, and number or the conjunction of tense, person, number, and gender. For example, “you (masculine) rode” and “you (feminine) rode” have different inflections, shown in raxavta and raxavt, respectively. “He rode” and “She rode” are also inflected differently from each other (raxav and raxva, respectively) and from the second person inflections. Yet “I rode” carries the same inflection (raxavti) regardless of the gender of the speaker, and “They rode” (raxvu) employs the same inflection independent of the gender of the referents. Dromi et al. (1999) reasoned that if processing capacity is limited in children with SLI, differences between these children and MLU controls (favoring the

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latter) would be greater for those inflections involving the conjunction of four dimensions (such as past third person singular feminine) than for those inflections involving the conjunction of only three dimensions (such as past first person singular or past third person plural). The findings were consistent with this expectation. This difference could not be attributed to any one dimension, such as gender. For example, within present tense, Hebrew inflections differ only according to gender and number. Yet the children with SLI were as proficient as MLU controls in using these inflections. Thus far, I have discussed how processing limitations might lead to differences in degree of use of individual morphemes. It also seems possible that such limitations can lead to differences in the degree to which whole syntactic frames associated with particular morphemes might be used. Earlier, I noted that incompletely processed material might lead to the retention of sentence-final clauses in the input, such as Her running, and that these might be taken as acceptable main clauses by the children. Eventually, after children have had enough successful (fully processed) encounters with tense/agreement morphemes, these nonfinite frames will be reserved for subordinate clauses (as in We saw her running). However, with a history of producing such frames, children with SLI may well retrieve these highly accessible frames during instances of high processing demands, such as when some of the words in the sentence to be produced are relatively unfamiliar to the child, when the child must produce the sentence quickly, or when the child’s attention shifts to some other detail in the speaking context at the time of the utterance. This possibility was explored by Leonard et al. (2002). Upon examining the data from the Leonard et al. (2000) syntactic priming study discussed earlier, these investigators noted that if children with SLI happened to omit the auxiliary form during their repetition of the experimenter’s prime sentence (e.g., repeating The cats are drinking the milk as The cats drinking the milk), they were highly likely to omit the auxiliary in their description of the target picture (e.g., describing a picture as The fox chasing the dog rather than as The fox is chasing the dog). In one sense, this was unexpected. If children were attempting to produce the appropriate syntactic frame during the repetition of the prime sentence, this frame should have been activated, even if they did not manage to include the auxiliary form in their attempt at the prime sentence. This activated frame, which was appropriate for the target picture to follow, should have shown some facilitative effects. Specifically, the activated frame should have contained a slot for the auxiliary form and due to the ease of retrieval of the frame thanks to the priming, resources should have remained for the retrieval of the auxiliary form during the production of the target sentence. The fact that this did not occur suggests that children may have been attempting a different syntactic frame during their auxiliary-less productions of prime sentences. The most likely candidate would be the corresponding nonfinite frame, which may have predated the appropriate finite frame in the children’s

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production history. Given children’s strong tendency to describe the target picture without an auxiliary after having produced a prime sentence in this manner, the target sentence production may well have reflected priming, but of a different sort than anticipated, namely, priming of a nonfinite syntactic frame. To examine this possibility, Leonard et al. (2002) added a nonfinite prime condition to the conditions used in the prior study. This was done by showing the child a picture, asking the question “What do you see?” followed by the prompt “We see ...,” and having the child repeat a nonfinite clause (e.g., “We see . . . the horse eating the grass”). Other prime conditions included an auxiliary are prime (e.g., The girls are flying the kite) and a past tense prime (e.g., The bird flew away). As in the earlier study (Leonard et al., 2000), children’s target picture descriptions (e.g., The mouse is reading a book) were much more likely to include the auxiliary is when the target followed the auxiliary are primes than when it followed the past tense primes. The lowest percentage of auxiliary is use occurred when the preceding prime was nonfinite. Note that the context created for the target picture description (showing a picture and asking “What’s going on now?”) should have promoted use of an auxiliary. The fact that an auxiliary was often missing from the target picture description if a nonfinite prime preceded the target suggests that children had difficulty retrieving an appropriate frame when an established (though less appropriate) competitor frame was more readily available. The reduction in the processing demands associated with the nonfinite frame due to its prior activation was apparently the principal influential factor. In summary, we have seen how processing demands may contribute to low degrees of use of grammatical morphemes and even whole syntactic frames that accommodate these morphemes. Gradually, with additional adult input and growth of processing skills, children with SLI will show higher degrees of consistency in achieving the appropriate forms. Unfortunately, mastery levels are usually not achieved until well into the school years (e.g., Rice, Wexler, & Hershberger, 1998), and individual cases can be found in which inconsistency continues into early adulthood (van der Lely, 1997). Future research will need to determine the reasons for such residual difficulties. Certainly one possibility is that they are the result of continued processing limitations. Another possibility is that children’s processing ability eventually reaches a level that could support adult-like morphosyntax but does so only at an age that exceeds the optimal neuromaturational period for this type of attainment. The latter possibility has some parallels in findings that older learners are less proficient in learning a second language than younger learners. In the SLI case, processing limitations might endure through most of the optimal period for learning language such that when processing ability finally reaches a level that could ordinarily sustain adult-like language, language learning is no longer an efficient process and/or compensatory mechanisms have to be recruited.

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V. Implications What are the broader implications for the study of SLI if processing limitations prove capable of accounting for significant details of the language impairment? One implication pertains to differential diagnosis of language disorders. In particular, a clinical distinction is made between children with SLI and children with “nonspecific” language impairments (NLI), that is, children with language impairments along with nonverbal IQs that fall slightly below the average range. The evidence reviewed in this chapter coupled with comparisons between SLI and NLI groups suggest that, rather than differing qualitatively, children with SLI and those with NLI may differ principally in the severity of their processing deficit. Several observations support such a position. First, recall that children with SLI often show slower response times and poorer performance on working memory tasks than typically developing peers even when the tasks are nonlinguistic in nature (e.g., Hoffman & Gillam, 2004; Johnston & Ellis Weismer, 1983; Miller et al., 2006). Furthermore, close inspection of the literature reveals that children with SLI are more likely to earn nonverbal IQ scores in the belowaverage range of 85–99 than are their typically developing peers (see Leonard, 1998). In typically developing children and adults, individual differences in nonverbal intelligence test scores are predicted quite well by performance on working memory and processing speed tasks (Fry & Hale, 1996). Because tests of nonverbal intelligence often involve reasoning processes along with the storage of information, one can argue that working memory and processing speed are primitives, not nonverbal intelligence. Johnston (1982) found that children with SLI appear to score as well as they do on nonverbal intelligence tests because they succeed on items that require the visual matching of static figures, shapes, and designs, especially when all stimuli remain in view and no time requirements are placed on the children’s responses. On items that depend more heavily on processing speed or working memory, these children do not appear to perform as well. Comparisons between children with SLI and children with NLI on speed of processing tasks reveal slower response times for the children with NLI. However, in other respects the two groups are quite similar. For example, children with NLI resemble children with SLI in their response time pattern across linguistic and nonlinguistic tasks (Miller et al., 2001; Miller et al., 2006). Children with NLI also earn significantly lower scores on tests of language than do children with SLI (e.g., Miller et al., 2006), yet their language profiles of relative strengths and weaknesses do not differ from those of children with SLI (Tomblin & Zhang, 1999). Together, these observations suggest that the distinction between the SLI and the NLI groups is principally one of degree. Children with NLI have

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weaker processing abilities than children with SLI and this, in turn, might contribute to their lower nonverbal IQs and poorer language scores relative to children with SLI. Children with SLI are not as limited as children with NLI in processing ability, but are nevertheless below age level in this regard. Although language seems to be the weakest area in these children (though they are less impaired in language than children with NLI), close inspection reveals that nonverbal intelligence is not as strong as the designation of “average intelligence” might suggest. The notion that children with SLI and those with NLI might not be qualitatively different receives support from other quarters. In particular, genetic studies of twins have revealed that discrepancy scores (marking the difference between nonverbal intelligence and language test scores) show only a minimal level of heritability and hence “may not reflect the underlying genetic influences involved in SLI” (SLI Consortium, 2002, p. 395). To be sure, genetic factors underlying the language impairment reflected in SLI will be discovered; however, they may not prove to be distinct from those related to NLI and are likely to implicate abilities that extend beyond language itself.

VI. Conclusions In this chapter, I have tried to illustrate how processing difficulties in children with SLI—in the form of speed of processing limitations and limitations in working memory—may contribute to these children’s language impairment. These processing difficulties may slow the rate of these children’s language development more generally, but also may be important factors in leading some areas within language to be more seriously impaired than others. Furthermore, when processing limitations are viewed in interaction with both typological distinctions among languages and the adult input available to children, one can provide a reasonable account of the crosslinguistic differences seen in SLI. Finally, by considering processing difficulties within the context of morphological paradigm building and the storage and retrieval of syntactic frames, a plausible explanation for differences in degree of use between children with SLI and younger typically developing children can be offered. A frequent criticism of processing-based approaches is that their great strength—breadth of application—is also their weakness due to lack of precision. In this chapter, I have endeavored to show how rather narrow, languagespecific morphosyntactic weaknesses can result from rather general deficits in processing abilities. Some of these ideas are speculative, supported by related research but as yet untested in their details. However, if proven accurate, they will provide an advantage over alternative approaches, as no others appear to offer a plausible explanation for pockets of serious difficulty layered over a broader baseline of mild to moderate deficiency in language ability.

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Acknowledgments The author’s work reviewed in this chapter was supported by Research Grant R01 DC00458 from the National Institute on Deafness and Other Communications Disorders, National Institutes of Health.

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Hsieh, L., Leonard, L., & Swanson, L. (1999). Some differences between English plural noun inflections and third singular verb inflections in the input: The contributions of frequency, sentence position, and duration. Journal of Child Language, 26, 531–543. Ingham, R., Fletcher, P., Schelleter, C., & Sinka, I. (1998). Resultative VPs and specific language impairment. Language Acquisition, 7, 87–111. Joanisse, M., & Seidenberg, M. (1998). Specific language impairment: A deficit in grammar or processing? Trends in Cognitive Science, 2, 240–247. Joanisse, M., & Seidenberg, M. (2003). Phonology and syntax in specific language impairment: Evidence from a connectionist model. Brain and Language, 86, 40–56. Johnston, J. (1982). Interpreting the Leiter IQ: Performance profiles of young normal and languagedisordered children. Journal of Speech and Hearing Research, 25, 291–296. Johnston, J. (1994). Cognitive abilities of children with language impairment. In R. Watkins & M. Rice (Ed.), Language impairments in children (pp. 107–121). Baltimore, MD: Paul H. Brookes. Johnston, J., & Ellis Weismer, S. (1983). Mental rotation abilities in language-disordered children. Journal of Speech and Hearing Research, 26, 397–403. Johnston, J., & Kamhi, A. (1984). Syntactic and semantic aspects of the utterances of languageimpaired children: The same can be less. Merrill-Palmer Quarterly, 30, 65–85. Kail, R. (1994). A method of studying the generalized slowing hypothesis in children with specific language impairment. Journal of Speech and Hearing Research, 37, 418–421. Kamhi, A., Catts, H., Mauer, D., Apel, K., & Gentry, B. (1988). Phonological and spatial processing abilities in language- and reading-impaired children. Journal of Speech and Hearing Disorders, 53, 316–327. Kilborn, K. (1991). Selective impairment of grammatical morphology due to induced stress in normal listeners: Implications for aphasia. Brain and Language, 41, 275–288. Kirchner, D., & Klatsky, R. (1985). Verbal rehearsal and memory in language-disordered children. Journal of Speech and Hearing Research, 28, 556–565. Lahey, M., & Edwards, J. (1996). Why do children with specific language impairment name pictures more slowly than their peers? Journal of Speech and Hearing Research, 39, 1081–1098. Leonard, L. (1989). Language learnability and specific language impairment in children. Applied Psycholinguistics, 10, 179–202. Leonard, L. (1998). Children with specific language impairment. Cambridge, MA: MIT Press. Leonard, L., & Bortolini, U. (1998). Grammatical morphology and the role of weak syllables in the speech of Italian-speaking children with specific language impairment. Journal of Speech, Language, and Hearing Research, 41, 1363–1374. Leonard, L., & Deevy, P. (2006). Cognitive and linguistic issues in the study of children with specific language impairment. In M. Traxler & M. Gernsbacher (Eds.), Handbook of psycholinguistics. New York: Elsevier. Leonard, L., Eyer, J., Bedore, L., & Grela, B. (1997). Three accounts of the grammatical morpheme difficulties of English-speaking children with specific language impairment. Journal of Speech, Language, and Hearing Research, 40, 741–753. Leonard, L., Hansson, K., Nettelbladt, U., & Deevy, P. (2005). Specific language impairment in children: A comparison of English and Swedish. Language Acquisition, 12, 219–246. Leonard, L., Miller, C., Deevy, P., Rauf, L., Gerber, E., & Charest, M. (2002). Production operations and the use of nonfinite verbs by children with specific language impairment. Journal of Speech, Language, and Hearing Research, 45, 744–758. Leonard, L., Miller, C., Grela, B., Holland, A., Gerber, E., & Petucci, M. (2000). Production operations contribute to the grammatical morpheme limitations of children with specific language impairment. Journal of Memory and Language, 43, 362–378. Loeb, D., & Leonard, L. (1991). Subject case marking and verb morphology in normally developing and specifically language-impaired children. Journal of Speech and Hearing Research, 33, 340–346.

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CHILDREN’S EXPERIENCES AND JUDGMENTS ABOUT GROUP EXCLUSION AND INCLUSION

Melanie Killen, Stefanie Sinno, and Nancy Geyelin Margie DEPARTMENT OF HUMAN DEVELOPMENT, 3304 BENJAMIN BUILDING, UNIVERSITY OF MARYLAND, COLLEGE PARK, MD 20742-1131, USA

I.

II.

INTRODUCTION A. DEFINING EXCLUSION B. OVERVIEW SOCIAL EXCLUSION BASED ON GENDER A. PREVALENCE B. EXCLUSION C. INCLUSION

III.

SOCIAL EXCLUSION BASED ON RACE/ETHNICITY A. PREVALENCE B. EXCLUSION C. INCLUSION

IV.

CONCLUSION

ACKNOWLEDGMENTS REFERENCES

I. Introduction Children experience inclusion and exclusion from social groups throughout childhood and adolescence. The consequences of these experiences have implications for becoming a member of a culture and society. Extensive experience with exclusion has long-term negative consequences, such as depression, anxiety, and social withdrawal, for those who are excluded, and conduct disorders, criminality, and antisocial behavior, for those who do the excluding. However, an orientation toward inclusion has long-term positive consequences, given the increasingly global and multicultural nature of the workforce and higher education and the increasing migration of individuals across traditionally identified national boundaries. Inclusion and exclusion are pressing and timely topics regarding global and intercultural relationships, and understanding the developmental origins of these experiences is central for facilitating positive and healthy adult social relationships (Abrams, Hogg, & Marques, 2005; Killen, Margie, & Sinno, 2006).

173 Advances in Child Development and Behavior R.V. Kail : Editor

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Despite the fact that children’s peer relationships constitute an extensive area of research in developmental psychology, only since the 1990s have developmental researchers focused on children’s experiences with exclusion and inclusion from an intergroup perspective. This involves investigating how (and when) children and adolescents relate to peers differently as a function of their group membership, such as gender, race/ethnicity, and culture. This topic has been studied extensively in adult populations by social psychologists, and research with children indicates that the findings have direct relevance for many substantive areas of children’s social development (Levy & Killen, in press). Developmental research on peer rejection (Bierman & Wargo, 1995), victimization (Juvonen & Graham, 2001), and bullying (Olweus, 1993) reflects important lines of peer relationship research that have direct bearing on understanding processes of inclusion and exclusion. Research on children’s exclusion in the forms of rejection and bullying has typically focused on individual differences, such as investigating how children at extreme ends of the social continuum become vulnerable (shy and fearful) or aggressive (aggressive and insensitive to social cues) toward others and thus are at risk for becoming victims or bullies. In other words, research has been aimed at understanding the personality and social characteristics of individual children (and aspects of the individual–group relationship) that contribute to predicting which children are vulnerable to being the recipients or perpetrators of socially deficit actions. To the extent that these lines of work have focused on group processes, the emphasis has been on how the individual child understands group processes, such as peer group entry rituals, conflict resolution, and reading social cues (see Bierman, 2004; Rubin, Bukowski, & Parker, 2006). These findings have demonstrated that social competence is a key aspect of how rejection and exclusion processes emerge, evolve, and are perpetuated in children’s social interactions. An intergroup approach to exclusion and peer relationships complements these lines of work and extends the field in new directions by investigating when and how children experience exclusion and inclusion as a function of their group membership. Moreover, investigating these forms of inclusion and exclusion opens up a window into the developmental origins of prejudice, stereotyping, and biases, the bases on which exclusion based on group membership are founded. This type of understanding provides a foundation for determining when stereotypes and negative biases emerge in child development and how it might be that educators, parents, and adults can intervene to diminish negative biases that contribute to societal conflict at the adult level (Killen et al., 2006). Research drawing on social psychological theories of social identity and categorization (Abrams et al., 2005; Nesdale & Brown, 2004; Rutland, 2004) and intergroup contact theory (Dixon, Durrheim, & Tredoux, 2005; Pettigrew & Tropp, 2005) has revealed that children’s exclusion and inclusion decisions reflect intergroup attitudes and are often a function of their social experience.

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Although many forms of exclusion occur between children (e.g., obesity, handicap, religion, nationality), most of the research in the United States has been conducted on exclusion based on gender and race/ethnicity, and thus, these areas constitute the focus of this chapter. Furthermore, gender and race/ethnicity are categories that, for the most part, individuals cannot change. In general, gender and race/ethnicity have reflected patterns of exclusion, prejudice, and bias for most of the history of humankind.

A. DEFINING EXCLUSION Exclusion occurs at many levels of social interaction. Social psychological theory and research have identified intrapersonal, interpersonal, intragroup, intergroup, and institutional forms of group inclusion and exclusion (Abrams et al., 2005). Events at these levels of human functioning range from exclusion that occurs during a children’s playground game to exclusion that occurs when one country expels a group of people from its lands, leading to homelessness and genocide (Opotow, 1990). In addition to the scope of these events, exclusion varies in terms of the basis for exclusion, the context, the intentions, and the group dynamics. The focus of this chapter is specifically intergroup exclusion based on gender or on race/ethnicity. Within the intergroup context, exclusion is a multifaceted event. These facets are evident when children’s and adolescents’ social reasoning about exclusion is examined. The theoretical model that guides this multifaceted view of the social reasoning behind exclusion is referred to as a social domain theory, and this approach has guided our research. In brief, social domain theory (see Nucci, 2002; Smetana, 2006; Turiel, 1998, 2006) proposes that social knowledge reflects different domains of reasoning: the moral (fairness, justice, rights, others’ welfare), the social–conventional (group norms, customs, traditions), and the psychological (self-understanding, individual discretion, personal choices). Judgments about morality have to do with how individuals ought to behave toward one another, and violations of morality often focus on the negative intrinsic consequences of the action. Social conventions are culturally specific norms used to regulate social interactions, established through consensus (unlike moral norms), and serve to ensure smooth group functioning and expectations. Psychological decisions are matters of personal choice, such as hair length, nicknames, choice of friends, and choice of marriage partners, and are not regulated norms in the way that moral and conventional rules are. Extensive research with individuals in multiple cultures (i.e., United States, United Kingdom, Japan, Korea, China, Spain, Turkey, Nigeria, El Salvador, Colombia, Virgin Islands, Germany, India) has revealed that children, adolescents, and adults use the same underlying criteria to determine whether an act is

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moral, social–conventional, or psychological, particularly when evaluating prototypic issues within each domain (Helwig, 2006; Wainryb, 2006). In addition, this model has been applied to complex issues, revealing the ways in which individuals differ in how they categorize and evaluate social events. Our research program has focused on how individuals evaluate exclusion and inclusion, documenting when exclusion is viewed as a moral transgression, when it is viewed as serving a conventional function, and when it reflects primarily a psychological decision (see Killen et al., 2006, for a review). Some forms of exclusion, such as peer rejection and victimization, are clearly viewed as moral, in that decisions to exclude are unfair, are harmful, and deny individuals equal treatment. There are also times when exclusion can be viewed as social–conventional, in that decisions to exclude are agreed upon by all of the individuals participating and are designed to make groups function well. Examples of socially condoned exclusion could be exclusion from a sports team for being a poor athlete, from college for low grades, or from academia for a lack of a publication record. Moreover, exclusion is sometimes viewed as a personal prerogative, such as the choice of a friend or marriage partner, which leads individuals to categorize such decisions as personal and up to individual discretion. When intergroup exclusion, such as exclusion based on gender or on race/ ethnicity, is explained in terms of social–conventional and personal reasoning, however, careful analyses are required to differentiate these forms of reasoning from stereotypic attitudes that are often reflected by conventions and individual prerogatives. For example, “Girls should take cooking classes because then they can be good mothers” reflects conventional reasoning about gender roles as well as stereotypic expectations about gender traits. A response that encompasses stereotypes makes for a complicated set of issues that involves difficult consequences for those being judged, including exclusion based on discrimination, rather than social conventions or group functioning (see Table I for justification categories and examples). The social domain method takes these different orientations into account in analyses of social reasoning. Stereotypes are judgments about an individual’s traits or behaviors based on group membership. Researchers tend to conceptualize stereotypes as dependent on cognition (Aboud, 1988). Regardless of their stated beliefs about other groups, children’s (and adults’) cognition is impacted by an awareness of stereotypes. In addition, it is difficult to change an individual’s adherence to stereotypic beliefs. For instance, children are better able to remember stereotypic information than counterstereotypic information (Bigler & Liben, 1993). Children who are better able to remember counterstereotypic information, though, are also less likely to endorse stereotypes (Bigler & Liben, 1993). A major concern of stereotyping, therefore, is that after generalizations are made

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about people based solely on their group membership, these generalizations can be unfairly applied to individuals from that group (Killen et al., 2006). This then can lead to discrimination. Discrimination often occurs as a behavioral manifestation of stereotypes and specifically as negative behavior toward outgroups (Brown & Bigler, 2005; Romero & Roberts, 1998). Discrimination, or differential treatment based on biased beliefs about one’s group membership, can restrict academic, social, and career opportunities for those who are discriminated against. In addition, children and adolescents who experience discrimination report high levels of emotional problems, depression, and stress and low levels of selfesteem (DuBois & Hirsch, 1990; Simons et al., 2002; Szalacha et al., 2003; Taylor & Turner, 2002). It is essential therefore to investigate the social reasoning that individuals use when excluding others from a group, because exclusion based on functionality versus exclusion based on stereotypes can have very different effects. An intergroup approach includes understanding how children view the ingroup and the outgroup and how these types of attitudes and relationships emerge in early childhood and continue throughout adulthood. Research stemming from social identity theory (Tajfel & Turner, 1979) and social categorization theory has examined ingroup/outgroup attitudes in childhood, particularly regarding exclusion using categories based on nationality, not gender or race and ethnicity. As an example, and for future application to the categories reviewed in this chapter, these findings have revealed that children’s awareness of peer group dynamics reveals the powerful influence of children’s evaluations of group norms (Abrams, Rutland, & Cameron, 2003). In fact, these studies have shown that with age children dislike ingroup members who do not conform to conventional group norms such as supporting the team success of an ingroup. Furthermore, with age, children differentially evaluate norms expressed by ingroup and outgroup members and display a preference for individuals who support group norms (Rutland, 2004). Older children have an understanding of group dynamics in an intergroup context. Investigating children’s perceptions of group dynamics—that is, what makes the group “work well”—provides an indepth understanding about ingroup and outgroup relationships and the ways in which exclusion decisions manifest for children in peer settings. Following the tradition of drawing on social psychological theories, Nesdale and Brown (2004) have shown how the development of children’s prejudice is significantly influenced by their memberships in different types of peer groups. Again, although the focus was not explicitly on gender or race, Nesdale (in press) has shown that children who are rejected by peers are often more likely to display prejudicial attitudes than are children who are not rejected.

Examples

Wrongfulness of prejudice, discrimination, and unfair treatment regarding group membership

Gender • It’s wrong not to let her join just because she’s a girl; it’s a form of prejudice • There are no differences between boys and girls when you have to pick someone for the club and I think they should be treated equally

Moral

Gender or race/ethnicity • He does not even know him yet, so he cannot really judge him • She should not judge people on what they like to do; you should give them an equal chance

Social–conventional Conforming to peer pressure; the preservation of group functioning

Gender • The other boys do not want a girl in the club so he should not do it or he will lose his friends • Sometimes you need to have your own club to make it work, and that means you have to have a lot in common so everyone gets along Race/ethnicity • If it makes his friends mad, he should not hang out with a girl who is a different race; it would make his friends feel weird

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Race/ethnicity • It’s bad to exclude because all races are equal • You should not exclude someone based on skin color because that does not tell you who they are inside and then it would be unfair

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TABLE I Justification Categories for Analyzing Social Reasoning about Gender and Racial/Ethnic Exclusion

Status quo, current practices and traditions

The other kid might have different interests and if he does not fit in with the group then it will not work well because they will not know what to expect

Personal choice Individual decision making and prerogatives

Gender or race/ethnicity • It is your choice what you want to do • It is up to him and whatever he wants to do

Note: For reviews of the methods that employs these categories, see Killen et al. (2002) and Smetana (2006). Justification categories are typically coded from individually administered interviews or surveys in response to follow-up probes, such as “Why?” regarding decisions about exclusion. Reliability coefficients range from 0.80 to 0.98.

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Race/ethnicity • Black people like different music than White people so they do not have much in common • If she is Korean then they might not want her in the club because she will be too quiet

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Gender • Most people in this school think that boys and girls should have different teams and it is not good to mix it up • Boys and girls have never been in the same club before so why start something new Race/ethnicity • That is how it has always been done even before my parents’ time • Blacks and Whites did not hang out with each other before, why should they now

Attributing traits to individuals based solely on group membership while ignoring intragroup variation

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B. OVERVIEW Overall, our goal is to describe research on the prevalence of gender and of racial/ethnic exclusion in children’s lives and then to describe research findings from nonsocial domain perspectives that have documented the contexts in which children experience social exclusion based on gender or race/ethnicity. Although nondomain approaches have not focused on children’s social reasoning about these experiences per se, the findings reveal the prevalence of exclusion and how exclusion varies by group membership. This research also provides information about the sources of exclusion in the family, peer groups, and school, as well as experiences that facilitate inclusion (i.e., buffers and factors that enable children to take inclusive, rather than exclusive, perspectives toward others). Throughout each section, we describe social domain model research on exclusion and inclusion, highlighting what we have learned from investigating children’s reasons for exclusion and inclusion decisions made by peers and parents. Our social domain model provides a method for understanding how individuals evaluate decisions to exclude, as well as decisions to include, and the underlying reasoning for this type of decision making. We have a caveat about the research that we review in this chapter, which, although common in the literature, is particularly relevant to our topic of exclusion. By far, the vast majority of the research we describe has been conducted in North America, Australia, and Europe. In other parts of the globe, gender exclusion, for example, is much more pervasive in daily life than is apparent in the countries that study the phenomenon (see Nussbaum, 1999; Turiel, 2002). In addition, the unique history of the United States—with slavery and immigration making skin color particularly salient—has generated an explicit focus on children’s exclusion experiences based on race/ethnicity in the United States (along with immigration patterns in Europe that bear on research programs in this area). Thus, given that the vast majority of social science and psychological research on the topic of exclusion has been conducted in North America and Europe, we report our findings with the expectation (and hope) that these models will eventually lead to new lines of research in other parts of the globe. Thus, this chapter is organized into three broad sections: (1) exclusion and inclusion based on gender, (2) exclusion and inclusion based on race/ethnicity, and (3) new directions. In the first two sections, we describe research on the factors that contribute to exclusion as well as the factors that contribute to inclusion. In addition, we highlight the importance of using a social domain model to understand further the reasons underlying exclusion and inclusion. As a conclusion, we will describe areas in which future research about exclusion and inclusion could benefit from the social domain theory of social reasoning.

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II. Social Exclusion Based on Gender A. PREVALENCE Research on social exclusion based on gender focuses on the limitations experienced by children, because explicit restrictions have greatly diminished over the past half-century with the emergence of laws and legislation protecting individuals from gender discrimination (Gaertner & Dovidio, 1986). Nonetheless, by limiting certain experiences based solely on gender, such as playing with gender-identified toys or engaging in gender-identified skills and academic arenas, individuals are less likely to develop skills related to these domains and feel less competent in these roles (Leaper, 2002). In turn, individuals can become limited to roles that they have been made to feel they should be best at based on their gender. Many of these roles, prescribed by societal standards, are reflected in children’s social environment and are pervasive in the adult world. From a young age, children often experience differential treatment from their parents, particularly regarding play activities (Lytton & Romney, 1991). Limiting children from any task that may be considered atypical of their gender, however, affects the development of later useful skills. For instance, sports, which are greatly encouraged in young boys, teach instrumental skills; whereas sociodramatic or role play, encouraged more for girls, teaches compromising and communication skills (Leaper, 2002). Following this line of thought, as children age, their play groups become separated by gender and the interactions afforded to their socialization become limited. Girls are encouraged to engage in dyadic relationships and boys are encouraged to play in groups (Maccoby, 1998). In school, children’s ability to do well in certain academic domains is often affected by gender expectations. Some parents and teachers assume that boys perform better in math and girls perform better in reading, leading children to question their competence in these domains because of their gender (Jacobs et al., 2002). Furthermore, these self-evaluations of competence in math and science deter girls from continuing classes in these subjects and limit their options for college majors, as has been demonstrated by extensive research on children’s motivation and academic development (see Wigfield et al., 2006). Parental encouragement of both masculine and feminine tasks for both male and female children has been shown to lead to an increase in their children’s interest in a wider variety of cross-gendered activities (Antill et al., 1996). Interests in a wider array of activities opens children’s opportunities to experience life more fully, as well as enhancing their ability to make more educated decisions about their future goals. Career paths are often gender identified for children, resulting in a different type of exclusion. For tasks that are traditionally male oriented, as is often the case in high-powered careers, females are seen as less competent and need to complete more job-related tasks to prove themselves

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(Biernat & Kobrynowicz, 1997). This segregation in the workforce often more directly affects adults with families. Mothers are seen as less competent at working and more competent at nurturing and childcare, whereas fathers are expected to be the ideal worker for a company because they should be the primary financial provider for the family (Fuegan et al., 2004). These diverse experiences contribute to children’s acquisition of gender identity, roles, and stereotypes. As noted previously, stereotypes are defined as attributes assigned to individuals based solely on a group membership, such as gender. At the same time that children acquire stereotypes, children develop notions of equality, fairness, and justice (Turiel, 1998), and how these forms of knowledge are coordinated with their emerging gender-specific concepts constitutes part of the social reasoning model research program. Experiences with exclusion and inclusion affect the developmental relationships of children, within their homes and peer lives. In the next section, we discuss the consequences of gender exclusion and then discuss gender inclusion and its benefits. We approach these sections in terms of developmental shifts that begin with experiences of gender in the home and within in the family context, followed by the peer context, which is primarily school-based, and conclude with the context of academic and work avenues.

B. EXCLUSION 1. Family Contexts The first environment in which children have access to witnessing exclusion based on gender roles is in the home. Okin (1989), a political philosopher, argues that while moral philosophers have theorized that concepts of justice emerge out of parent–child relationships, throughout the centuries, the family has reflected a social context often lacking in gender equality and equity. Although gender roles in developed nations have changed dramatically since the 1960s, parental division of chores in the home remains fairly gender stereotyped and gender divided. For example, many more women have made inroads in male-dominated careers, such as medicine and engineering (Caplow, Hicks, & Wattenberg, 2001), and many men have increased their responsibility for household chores (Bond et al., 2003; Coltrane, 1996). Nonetheless, men are expected to assume the role of breadwinner and to be an “ideal worker,” often spending over 40 h a week at work (Williams & Cooper, 2004), and mothers, including full-time career women, are expected to perform a majority of the household chores (Douglas & Michaels, 2004) and spend most of their time with the children (Center for Demography and Ecology, 1992–1994). Parental division of labor in the home and chores assigned to children is a significant area in which roles and tasks are divided along gender lines. Daughters in many families do more feminine tasks, such as washing dishes or vacuuming,

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and boys do more masculine tasks, such as taking out the trash (Antill et al., 1996; McHale et al., 1990). Also, tasks in the home thought to be acceptable for children depend highly on family makeup (Crouter, Manke, & McHale, 1995). If a family has a daughter and a son, parents might see it as more deviant if the daughter was interested in stereotypic male activities and the son was interested in more female stereotypic activities, in comparison to families with only boys, only girls, or just one child. These findings are more salient for parents who are mostly limited in roles appropriate to their own gender because they most often divide labor among their children according to these gender differences (Blair, 1992). Differences in chore assignment based on gender have also been related to sex-role attitudes. In families in which girls held much more responsibility than boys for chores, a large gap in sibling sex-role attitudes emerged, with boys having more traditional beliefs (Crouter et al., 2001). Although children, like adults, categorize the genders based on societal expectations, children understand issues of fairness and equality in gender-exclusive contexts (Killen et al., 2006). Research based in social cognitive domain theory, therefore, has looked at children’s reasoning about gender exclusion in the household. Theimer-Schuette (2000), for example, asked children to evaluate a parent’s decision not to ask a child to help with a chore when it was gender inconsistent (e.g., the son to help sew curtains; the daughter to help change the oil in the car). Children relied on gender stereotypes when that was the only information presented; however, they were more likely to accept cross-gender behavior when the fairness of the situation was made salient (Theimer-Schuette, 2000). This study showed that although children relied on stereotypes to evaluate parents’ decision, this reliance decreased with age and was rejected when fairness concerns were considered. Children also reason differently about the parental household roles of caretaker and breadwinner, based on gender of the parent and the role in question (Sinno & Killen, 2006). Overall, young children (6- and 9-year-olds) viewed it as unfair for one parent to disagree with the other’s decision to take on a caretaking or a breadwinner role solely because of his or her gender. In addition, children believed that both mothers and fathers should be able to have a full-time job, for personal choice reasons. Yet, comparing mothers’ and fathers’ decision to stay home and take care of a new baby, children were more likely to respond that it would be better for the mother to stay at home. Furthermore, children invoked gender stereotypes about mothers’ natural abilities to justify why the father should not stay at home, including that the mother would know more about the baby, would be more loving, and would know more about caretaking activities (e.g., feeding and changing diapers). Children who thought it was okay for the father to stay at home with the new baby said so because of family functioning and practicality. For example, the mother may make more money, making it better for the father to stay at home (see Figure 1).

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Proportion of Reasons

0.6 0.5

Social Conventional

0.4

Gender Stereotypes

0.3

Personal Choice

0.2 0.1 0 Mom at Work Dad at Home Parental Target Role

Fig. 1. Proportions of children’s justifications for evaluations of nonstereotypical parental roles.

Findings from this study further the notion that decisions about gender exclusion are multifaceted. In the context of parental roles, children treat the role of breadwinner as equally acceptable for mothers and fathers; however, for the role of caretaker, children rely more heavily on gender expectations and therefore reason that the role is more appropriate for mothers, as shown in Figure 1. Children do not always rely on stereotypes or personal experience to explain division of labor in the home. Rather in some contexts they focus on issues of morality and fairness, in others they focus on conventions or group norms, and in others they focus on personal choice. Again, although division of labor may lead to exclusion, there are many reasons children see it as acceptable or unacceptable. The experience of exclusion based on gender expectations is not only witnessed by parental division of labor but also personally experienced by children through parental expectations of their male and female children. Signs of parental expectations for their children begin as early as infancy. In regard to emotions, mothers respond more consistently to their sons’ emotional outbursts than to their daughters’ (Biringen et al., 1999). In looking at adults’ beliefs about gender emotionality, in which women are expected to be more emotional than men (Plant et al., 2000), mothers may be attempting to tame their sons’ emotions to help them fit societal expectations and to behave more masculine. At an older age, parents offer daughters more opportunities for emotion talk (Leaper, 2002). In addition, the type of emotions discussed with children varies by gender, with conversations with boys including more references to anger and conversations with girls discussing issues of sadness (Fivush, 1991; Fivush et al., 2000). Many of these conversations may foster an expectation for girls to depend on parents (Lytton & Romney, 1991). That is, girls are encouraged to talk about their problems and seek solutions from their parents without trying to solve it themselves.

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Also, beginning in infancy and lasting through childhood, parents monitor or control toys and activities of their children. Some parents buy gender-stereotyped toys within the first few months of the child’s life, before the child indicates any preference toward one object or another (Pomerleau et al., 1991). By providing positive feedback, parents also are apt to encourage children to play with toys that are consistent with gender expectations. Boys often receive more negative feedback for playing with toys or participating in activities not typically considered masculine (for review, see Ruble & Martin, 1998). In fact, in a study in which parents and nonparental adults were interviewed about their reasoning regarding children’s decisions to engage in nonstereotypic peer activities, parents were less likely to condone nonstereotypic preferences (a boy taking ballet or a girl playing football) than were nonparental adults and used more conventional and stereotypic reasons than did nonparental adults, who based their decisions on autonomy and fair treatment (Killen et al., 2005). From an early age, then, children learn that certain roles are appropriate for them and may begin to feel limited in options for interest. Although they may not be explicitly excluded from using certain toys or engaging in certain activities, they may be made to feel that toys and activities are inappropriate because of their gender. Messages from adults about appropriate toys and activities emerge in children’s own categorization based on gender expectations. Martin, Wood, and Little (1990) showed that 4- to 6-year-olds predicted the gender of a child whose sex was not mentioned by a target characteristic of toy preference. At this age, children were better at identifying the gender of the unknown child if the characteristic toy preference was stereotyped for their own gender. Despite the early acquisition of gender stereotypic associations with toy preferences and play activities, children view gender exclusion in peer contexts of play as wrong, due to the resulting unfairness and lack of equal treatment (Killen et al., 2001). In a study with 3½- to 5½-year-olds, children judged it as wrong for a group of girls to exclude a boy from playing with dolls or a group of boys to exclude a girl from playing with trucks; moreover, this judgment increased from preschool to kindergarten (Killen et al., 2001). Parents communicate messages about toy preferences, which transfer to peer activities but are reinterpreted by children as a function of their developing social knowledge and moral judgments. 2. Peer Contexts In their friendships, girls often report more kindness and empathetic understanding from peers than do boys, and boys report more emphasis on loyalty and commitment in their friendships than do girls (Clark & Bittle, 1992). Disentangling children’s expectations of their gender roles in the context of peer relationships from what actually goes on in their peer exchanges is difficult. Some of these expectations might be a result of parental expectations of gender emotionality. Or these expectations may refer to differences in traits assigned to

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males and females. Children often assign more positive traits and fewer negative traits to strangers of their own gender (Powlishta, 2001) and both adults and children view male traits as more adult-like and less childish then female traits (Powlishta, 2000). Children may feel more comfortable choosing same-gender friends who they would expect to have traits similar to theirs, and this, in turn, influences their expectations for choice of friendships. With these expectations of how boys and girls should interact with their peers, those who behave contrary to their norm in activities or interests might also be expected to be unable to provide their peers with the psychological benefits of a same-sex best friend. In particular, girls who behave in ways stereotypic of boys are labeled as “tomboys” and are seen to have both masculine and feminine qualities equally. Boys who behave in ways stereotypic of girls are labeled as “sissies” and seen as more feminine than masculine (Martin, 1995). In addition they are more often disliked by peers (Martin, 1989). Both boys and girls may assume, based on gender roles of friendships, that tomboys and sissies are unable to share an interest with their same-sex peer group. These assumptions can lead to the use of these labels to exclude peers based on their shift from gender norms (Sroufe et al., 1993). Boys who are nonconforming to gender expectations often experience more negative feedback than girls who are atypical (Bussey & Perry, 1982) and the consequences are more negative when boys cross gender norms than when girls do. Although children often exclude others based on nonconformity, Lee-Kim et al. (2006) found that sometimes children supported others’ preferences to engage in nonstereotypic activities. A difference between this study and previous research was that children were asked about parental restrictions on activities as a function of gender stereotype; with age, children disapproved of parents’ restriction on children’s choices. Thus, the source of decision for exclusion based on gender is related to whether children view it as legitimate. Furthermore, cultural differences emerged for boys’, but not girls’, preferences to engage in nonstereotypic activities: Korean children were more approving of boys’ desire to take ballet than were American children. These findings reveal that the extent to which exclusion decisions are viewed as unfair or legitimate is determined by the social context. A developmental shift in the use of gender stereotypes has been shown when children are questioned about the acceptability of partaking in cross-gender activities. In a study conducted with 5- to 13-year-olds, a U-shaped curve was found for acceptance of cross-gender activity (Stoddart & Turiel, 1985). Specifically, children in the youngest and oldest age groups thought that participation in a genderatypical activity was more wrong than did the children in middle childhood. The reasons children gave for their judgments differed, however. Younger children thought cross-gender behavior was wrong because it violated gender identity norms, but older children judged it wrong because it violated peer group expectations. The authors concluded that, in kindergarten, the maintenance of

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gender identity is defined in physical terms, so if a girl were to play a male stereotypic game, other children might question her gender. For adolescents, gender identity becomes closely linked to psychological characteristics, and behaving in a gender-atypical manner often leads to exclusion by others. Expectations for behavior, interests, and appearance based on gender are important in adolescence and those who are atypical in these areas are often ridiculed and harassed (Lobel, 1994). The strong adherence to these gender norms influences the opportunities available to the genders, by limiting the experiences that are acceptable for them to partake in. As noted by Horn (2006), adolescents who may be considered outside the norm of gender expectations might be willing to change themselves, therefore possibly not experiencing a broad range of interests; they may attempt to alter the beliefs of others, although often dealing with negative reactions; or they may remove their identity and values outside of the peer group completely, making them isolated and leading to a difficult life for a teen of not fitting in. Research conducted by Horn and colleagues (Horn, 2003; Horn, in press; Horn & Nucci, 2003) has focused on adolescent reasoning about gender exclusion and gender nonconformity. In a study on gender exclusion, adolescents were surveyed regarding their evaluations of excluding or denying resources to another adolescent when the individual did not fit stereotypes (e.g., denial of resources, student council denies a scholarship to a “jock”; exclusion, cheerleaders exclude a “goth” from joining the team). Overall, adolescents evaluated denial of resources to other adolescents as more wrong than exclusion and used moral reasons to justify their judgments. When evaluating exclusion situations in which no individuating information was provided (e.g., the skill level of the excluded individual was not known), adolescents more often relied on stereotypic expectations than when the individuating information was made explicit. Ninth-graders and boys more frequently evaluated exclusion and denial of resources as acceptable and used conventional reasoning or stereotypes in justifying their evaluations than eleventh-graders and girls. In another line of research, Horn (in press) provided evidence that both social identity and group status influence adolescents’ judgments about inclusion and exclusion. Overall, high-status group members are included in school activities more frequently than low-status group members. Adolescents who identified themselves as members of high-status groups, however, exhibited more ingroup bias in their choice judgments, were more likely to use conventional rather than moral reasoning in justifying their judgments, and were more likely to invoke stereotypes than other adolescents. Adolescents’ beliefs about personality characteristics associated with gender identity (e.g., sexual orientation) are related to their reasoning regarding harassment as well (e.g., Horn, in press; Horn & Nucci, 2003). For example, adolescents’ judgments and reasoning regarding harassment based on sexual orientation are related to their beliefs about the origins (e.g., biological,

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choice, socialization) and acceptability of homosexuality. Overall, these findings indicate that adolescents use multiple reasons to evaluate gender exclusion, ranging from moral (“It’s unfair”) to conventional (“He doesn’t fit in with the group”) (Killen, McGlothlin, & Lee-Kim, 2000; Killen et al., 2002). Exclusion in the peer context, based on gender norms, has long-term effects on social aspects of an individual’s life. Children with few friendships or feelings of peer acceptance are more likely to have lower self-esteem than are children with multiple friendships (Rubin et al., 2006). In addition, children’s social self highly influences their ability to adjust to the demands of school. Children who are socially rejected may have more concerns about making friends, or avoiding their critical peers, than performing well in class. 3. Academic and Career Contexts Gender expectations for academic success and career paths are influenced by both peers and families. Gender expectations about academic interests often stem from the peer group. In addition, parents have academic expectations for their children that often follow a gender-biased line. Parents’ beliefs about gender can also interfere with their expectations for their children in academics and sports, in that they may expect their children to be involved in interests that are in accordance with gender stereotypes. Eccles, Jacobs, and Harold (1990) found that when parents held gender-stereotyped beliefs about one gender being more talented in a particular domain, they were more likely to have lower expectations of their child of the opposite gender, and this in some ways affected how the child of the opposite gender performed. For example, a mother who believes that boys are naturally more talented than girls in mathematics will then expect less from her daughter in mathematics, and a self-fulfilling prophecy for the daughter could ensue. Children often have their own self-beliefs and competence beliefs about academics and sports activities. Younger children (first grade) are found to have more positive outlooks about their capabilities in various arenas. As children grow older (fourth grade), their concepts of their personal abilities differ by gender. Boys tend to have more positive competence beliefs in sports and mathematics than girls, whereas girls tend to have more positive competence beliefs in reading and music than boys (Eccles et al., 1993). Furthermore, girls are less likely to believe that they can work to be the best in their worst academic subject (usually math) than boys. Boys are less likely to think that they can improve to be the best in areas such as music or art (Freedman-Doan et al., 1993). Differences in academic ability most likely are due to both nature and nurture influences (Eccles, Barber, & Jozefowicz, 1999), including gender biases from parents, teachers, and peer groups. Children, then, may internalize these stereotypes and avoid areas in which there is a bias against them. If teachers and parents implicitly or explicitly support gender stereotypic expectations then this may limit children’s willingness to explore their full potential. A child’s doubt of

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his or her own abilities in academics and interests in the school years could limit his or her options for majors in college and his or her future occupations. The notion of stereotype threat (Steele & Aronson, 1995)—which can come from several outside influences, including parents, teacher, and peers—may additionally affect the performance and self-competency expectations of young girls and in some instances young boys. In middle and high school, a time when the grades of high-achieving students begin to drop (Wigfield & Eccles, 2002), students are also becoming more aware of group stereotypes. Stereotypes about females not performing well in math and males not performing well in reading or literature are pervasive. After students are aware of the stereotype against their own group, they feel threatened in situations in which their competence in the stereotyped area is being challenged. For instance, when given a mathematics test, women of intelligence equal to that of males in their class performed less well than the men. In this instance the female students seemed to be aware of the stereotype against women in math and their competence level was affected. However, when some of the women in the group were told that gender has never been found to affect the test scores, they scored at an equal or higher rate than the males in the group (Spencer, Steele, & Quinn, 1999). Simply feeling threatened by a stereotype can therefore lead to lower overall performance in certain subject matters even if the individual has been successful previously in the subject matter (Aronson & Steele, 2005). This has a large effect on high school students, who must begin to think about taking classes in high school which will benefit their college majors and eventually their careers. Adolescents’ awareness of stereotype threat has not been analyzed, and the extent to which they understand the consequences of stereotyping on performance would help identify the factors that lead some adolescents to be resistant and others to be vulnerable to stereotype threat effects (Richardson, Killen, & Jampol, in preparation). Academic influences surrounding children affect their attitudes toward genderspecific tasks and roles. Parents may encourage young girls and boys in school to work harder in classes that are more stereotypically gender appropriate (e.g., encouraging boys to do well in math and girls to do well in English). This can, in turn, pressure adolescents to pursue careers that are socially desirable for their gender, instead of careers that they have an intrinsic desire to pursue. In addition, parents may, knowingly or unknowingly, encourage their daughters to pursue less time-intensive and more “family-friendly” careers and encourage their sons to pursue more prestigious and less “family-friendly” careers (e.g., teaching for girls and being a doctor for boys). Last, gender bias in adult roles may change children’s feelings about the importance of their role to a future family. Boys may feel that they do not need to help as much with childcare or running the household because they will be expected to be the breadwinner, whereas girls may feel that motherhood must be their only priority and therefore they will avoid career paths that would inhibit their mothering role.

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Gender stereotypes, such as those that may be encouraged in the academic context, can lead to exclusion in the adult working world. Children are aware of gender differences in occupational attainment (Liben, Bigler, & Krogh, 2001). Children often make links between occupations and the job’s status in the culture based on whether it is a typical male or female job. School-age children rated occupations they interpreted as male oriented, such as being a doctor, as higher in status than occupations they interpreted as female oriented, such as being a teacher (Liben et al., 2001). Furthermore, children preferred occupations that were associated with their own gender; that is, girls preferred occupations such as teacher and nurse, while boys preferred occupations such as doctor and lawyer. In addition, work with adults has shown that females are seen as less competent and often must do more job-related tasks to be seen as a competent worker when performing tasks that are stereotypically male, and vice a versa (Biernat & Kobrynowicz, 1997). What is not known is whether children view it as fair or unfair to exclude someone from an occupation solely because of his or her gender. Based on research with young children about doll- and truck-playing, in which young children judge it as wrong for girls to exclude a boy from playing with dolls (or for boys to exclude a girl from playing with trucks) (Killen et al., 2001; Killen & Stangor, 2001), we predict that adolescents would view straightforward occupational gender exclusion as wrong, particularly for occupations that were weakly gender identified, and that stereotypes would enter into their judgments for occupations that were highly gender identified. How this would change with age, or be affected by the gender of the adolescent, remains to be investigated. The consequences of gender exclusion, or the limiting of opportunities to one gender, can affect individuals throughout the life span and in various contexts. As described previously, children are affected by gender exclusion in the home, by their peers, and in schools. These experiences in turn affect the decisions they may make about their future adult goals. In addition, gender exclusion continues in the adult world and many continue to abide by societal expectations of the genders rather than individual variations in people. Providing equal opportunity to children and adults, rather than limiting opportunities based on gender, could lead to benefits in each of the contexts covered here as well as a more well-rounded society of individuals. In the following section we address some areas of research that have highlighted the benefits of more inclusive home, peer, and academic settings.

C. INCLUSION 1. Family Contexts Within the family context, positive benefits of equal opportunities to all family members, regardless of gender, influence more egalitarian attitudes and values in the children, supporting Okin’s (1989) view that an egalitarian-based family

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structure is related to the development of justice concepts. For instance, family structure, with regard to parental working status, affects children’s own gender stereotyping. Dual-earning families have less traditional standards with regard to gender stereotypical roles (Hoffman & Youngblade, 1999). Children in dual-earning families are more likely to accept parents’ desires to participate in nonstereotypical parental roles, such as a father staying home to take care of his children, and are less likely to use gender stereotypes or societal expectations about parental roles (Sinno & Killen, 2006). In addition, boys and girls in families with employed mothers have less traditional gender role concepts (Hoffman & Youngblade, 1999). Furthermore, daughters from these environments have been positively affected in several ways; for example, they display more independent coping skills and obtain higher achievement test scores (Hoffman & Kloska, 1995). Beyond parental working status, fathers who take on gender-atypical family roles, such as childcare, have children who are less gender stereotypical about careers and occupations (Deutsch, Servis, & Payne, 2001). In addition, sons of egalitarian fathers are more accepting of female activities and less likely to associate them with a negative stigma. This is likely because egalitarian households provide both daughters and sons with diverse experiences related to careers and household responsibilities. Boys hold egalitarian views if and only if the son’s role behavior is congruent with his father’s sex-role behavior and attitudes (McHale et al., 1990). In addition, parental encouragement of both feminine and masculine tasks leads to an increased involvement by children in other crossgendered activities (Antill et al., 1996). Egalitarian households provide both daughters and sons with diverse experiences related to careers and household responsibilities. Also paternal attention and intimacy are positively correlated with children’s self-esteem, perhaps because paternal involvement in childcare gives both boys and girls a broader selection of interests in activities and subjects, which may influence their future career goals (Deutsch et al., 2001). The more variety of activities and subjects that children can choose from, the more opportunities they have to excel in one area, which can increase their self-esteem. As mentioned previously, self-esteem influences children’s ability to interact with their peers. If a child with a high self-esteem continues to believe the messages received by his or her family about gender equality, he or she will have a more open acceptance of others and a broader view of how their peers can and should behave. These children may be more accepting of those who cross gender norms and help to spread a notion of inclusion in the peer context. 2. Peer Contexts As mentioned earlier, social domain research has looked at children’s reasoning about inclusion of peers in regard to toy preference and play activities

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(Killen et al., 2001).When asked to decide who to include to play with dolls or trucks, children were evenly divided about whether to pick a child who fit the stereotype and gave a mixture of moral and social–conventional reasons. Children who picked a child to play who did not fit the stereotype were less likely to switch their judgments than were children who picked a child who fit the stereotype, indicating that social–conventional and stereotypic reasons were less stable than were moral reasons. As an example of how children’s reasoning shifts based on contextual parameters, young children view that having more experience with a toy should result in turn-taking regardless of stereotype fit. In contrast, having equal experience with a toy resulted in group functioning justifications when the toy matched stereotype expectations (Theimer, Killen, & Stangor, 2001). For example, if both a boy and a girl had equal experience with a doll, children would choose the girl to be included because she fits the stereotyped expectation. In fact, with age, children focus on group functioning as a basis for inclusion decisions regarding peer activities (Killen & Stangor, 2001). Social reasoning about gender-stereotypic peer activities has been investigated in adolescent populations. The goal has been to document more complex reasoning patterns regarding inclusion and exclusion. Inclusion and exclusion in adolescence involves a wider range of groups than in early childhood, with an increased focus on group dynamics, group functioning, and group identity. When evaluating exclusion from gender-stereotypic contexts, such as ballet and baseball, with age, adolescents focus on the skill level required to join the club. As an example, in a gender-stereotypic peer exclusion study, more 12-year-olds viewed it as legitimate to exclude a boy or girl who did not conform to gender-stereotypic expectations when he or she was not skilled at the activity than did 6- and 9-year-olds (Killen & Stangor, 2001). Many 6- and 9-year-old children stated that it would be positive to include someone who did not conform to the stereotype, even when not as skilled, to provide a new opportunity for the child (e.g., “Boys don’t get a chance to take ballet; even if he is not good at it, they should pick him.”). Overall, children judged peer exclusion based solely on gender stereotypes as wrong using reasons such as unfairness. Yet, when complex contextual parameters were introduced, particularly regarding group functioning, children used multiple reasons to explain their evaluation decision, including conventions and traditions, as well as unfairness. 3. Academic and Career Contexts Inclusion in the academic and career context has not been a frequent focus of research. Some research, however, indirectly highlights the benefits of inclusive school and work environments. For instance, coeducational private schools have been shown to have fewer instances of sexism apparent in the classroom and were more likely to promote gender equity in the classroom, among faculty

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members, and in personal student relationships (Lee, Marks, & Byrd, 1994). Promotion of gender equity within schools would most likely decrease the fear of stereotype threat in that all students are challenged to the same academic standards and all students are encouraged in their academic abilities, regardless of gender. In addition, teachers who promote gender equity may also make an effort to motivate their students to do well in classes that have been stereotypically difficult for them to succeed in (e.g., females in the sciences). When students are motivated by teachers and feel supported by their peers, their self-efficacy in the subject area improves as well as their performance (Wigfield & Eccles, 2002). Young females who chose science and engineering as career aspirations were more likely to have high educational aspirations, were encouraged to do well in all areas of school, and had higher self-esteem (Mau & Domnick, 1995). These females were able to choose areas of interest rather than being forced to choose a role based on gender expectations. As research from the social domain model has shown, investigating children’s reasoning about gender is of critical importance to understanding gender exclusion. Previous work on gender has highlighted many important factors of gender exclusion, including gender roles in the family context, gender categorization by peers, and gender stereotyping in schools and the workforce. In much of this research, however, there is no information on why individuals maintain gender roles, the reasoning behind their categorization, or what they think about the fairness of gender stereotypes. This information is currently being explored by social domain theory and continues to be a major focus of the research program. Understanding the social reasoning behind gender exclusion, in its various forms, will help to uncover the motives for judging one gender different from the other and provide researchers with a more comprehensive way to promote gender equity. Limiting an individual’s options for fulfillment in all aspects of life has been shown to be detrimental in many ways and the social domain perspective offers a guide to understanding if those who exclude others based on gender realize the repercussions of their actions. Gender is often a reason for social exclusion in the United States, but another intergroup context that has been pervasive in U.S. literature on exclusion is race/ethnicity. Research on racial/ethnic exclusion can be examined in contexts similar to those for gender exclusion, including family, peers, and school. Within the next section, we examine factors that contribute to both exclusion and inclusion based on race and ethnicity. In addition, as with the gender section, we highlight studies from the social domain model that have focused on children’s and adolescents’ reasoning behind exclusion and inclusion. Following the race/ethnicity section, we conclude by providing ideas for future directions in further understanding of social exclusion.

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III. Social Exclusion Based on Race/Ethnicity A. PREVALENCE Exclusion regarding race and ethnicity has been examined most explicitly by researchers investigating victimization, harassment, and discrimination. Overall, victimization research has found that children from minority racial/ethnic groups generally report experiencing exclusion because of their race/ethnicity more often than children from majority racial/ethnic groups (Verkuyten & Thijs, 2002). In addition, even when children from different racial/ethnic groups report experiencing peer exclusion in similar amounts, exclusion may involve race/ethnicity more so than other forms of victimization. In one study, Anglo-British and AsianBritish victims, while equally likely to have been excluded by their peers, were more likely to have been excluded or teased about their race/ethnicity (but not more likely to be teased in other ways or physically bullied) by opposite race/ ethnicity bullies. Specifically, 17% of Asian victims reported being excluded by Asian bullies but 60% reported being excluded by Anglo bullies. Similarly, 7% of Anglo victims reported being excluded by Anglo bullies but 53% reported being excluded by Asian bullies (Boulton, 1995). Similarly, research on racial/ethnic discrimination in children and adolescents indicates that children from racial/ethnic minority groups are more likely than children from racial/ethnic majority groups to report having experienced discrimination (Biafora et al., 1993). Some research has found that Asian-American adolescents report being discriminated against by their peers more often than adolescents of other ethnicities (Fisher, Wallace, & Fenton, 2000). Another indicator of racial/ethnic social exclusion and inclusion is the prevalence of cross-race friendship. Overall, children report having fewer cross-race friends than same-race friends (Aboud, Mendolsohn, & Purdy, 2003; Clark & Ayers, 1992; Hallinan & Smith, 1985). In addition, the likelihood that children of any race/ethnicity will have friends of other races/ethnicities decreases with age (Aboud et al., 2003; for an exception, see Howes & Wu, 1990). EuropeanAmerican children, in particular, prefer same-race over cross-race friends (Aboud et al., 2003; Clark & Ayers, 1992; Levy, 2000; Newman, Liss, & Sherman, 1983; Ramsey, 1991; Ramsey & Myers, 1990).

B. EXCLUSION Exclusion based on race/ethnicity can both cause emotional harm and unfairly limit opportunities (i.e., for friendships, experiences, careers) for those who are excluded. In the following section we review areas of the literature on race/ ethnicity that can contribute to understanding the problem of social exclusion,

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including (a) parental influence; (b) exclusion in peer contexts, specifically friendship segregation and bullying/victimization; and (c) exclusion in schools and communities. 1. Family Context The relation between parents’ and children’s racial/ethnic stereotypes, prejudice, and discrimination is complex. Allport (1954) proposed that racial attitudes were transmitted directly from parents to children, but other research has found no relation between parents’ and children’s racial attitudes, stereotypes, or prejudices (Aboud & Doyle, 1996; Ritchey & Fishbein, 2001). However, even if parents do not send explicit messages of racial/ethnic bias to their children, they may be implicitly sending messages by showing a preference for their ingroup (Devine, 1989; Edmonds & Killen, 2006; Katz & Hass, 1988). For instance, adolescents’ behavior toward members of outgroups is related to their perceptions of their parents’ racial attitudes. Specifically, ninth and twelfth graders from a variety of U.S. racial/ethnic groups (i.e., European-American, African-American, Asian-American, Hispanic-Latino, biracial) who thought their parents had a negative racial bias were more likely than students who thought their parents had a positive racial bias to say (1) that their parents had reacted negatively to a cross-race friend or cross-race date, (2) that they would not date someone of a different race given the opportunity, and (3) that they would not bring a cross-race date home (Edmonds & Killen, 2006). Therefore, although parents and their children may not share the same explicit racial attitudes, children’s perceptions of their parents’ racial attitudes can influence their behavior with peers of other races/ethnicities. 2. Peer Contexts a. Friendship Segregation. Children and adolescents experience social exclusion based on their race/ethnicity while interacting with their peers. Friendship segregation, defined as fewer cross-ethnic friendships than the number of opportunities for cross-ethnic friendships (Moody, 2001), is much more likely than intergroup friendship (Hallinan & Williams, 1989). Specifically, children and adolescents are six times more likely to have a same-race friend than to have a cross-race friend (Hallinan & Williams, 1989). Same-race peer preferences may be related to the tendency to categorize people by race/ethnicity and reinforced by racial/ethnic group stereotypes. Levy (2000) found that preference for same-race peers was positively associated with race schematicity (i.e., the use of race to organize and remember social information) for young European-American and African-American children. Adolescents’ choice of peer groups is influenced by racial/ethnic stereotypes (Kao, 2000). Specifically, stereotypes about racial/ethnic group

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abilities in academics (e.g., Asians are good at school, African-Americans are not) and extracurriculars (e.g., European-Americans are good cross-country runners, African-Americans are good track runners) restrict adolescents’ perceptions of acceptable choices of activities, which in turn impedes their association with cross-race peer groups. For example, an African-American student may decide to run track instead of cross-country because of the stereotype that African-Americans are better at track, whereas European-Americans are better at cross-country. This stereotype is further reinforced by the resulting racial/ethnic segregation on her school track and cross-country teams (Kao, 2000). Friendship segregation varies depending on the racial/ethnic composition of a school and on the type of contact between students of different races (McGlothlin, Edmonds, & Killen, in press). In general, attending a heterogeneous school is related to less negative outgroup bias (Aboud, 2003; McGlothlin & Killen, 2006; McGlothlin, Killen, & Edmonds, 2005), and cross-race friendships between African-American students and European-American students are generally more likely as the two groups are equally represented in a school (Hallinan, 1982; Hallinan & Smith, 1985; Patchen, 1982; Quillian & Campbell, 2003; Schofield & Sagar, 1977). However, attending a heterogeneous school does not necessarily produce cross-race relationships (Moody, 2001). Specifically, using a nationally representative sample of more than 90,000 U.S. seventh through twelfth graders, Moody (2001) found that friendship segregation was least likely in homogeneous schools and in extremely heterogeneous schools (where more than two races/ ethnicities were represented) but most likely in moderately heterogeneous schools (where only two races/ethnicities were represented). Moody (2001) also found that friendship segregation is less likely when people of different races/ethnicities mix in extracurricular activities and in academic tracks. Therefore, type of contact, in addition to opportunities to interact with students of different races, is important for reducing friendship segregation. To examine children’s and adolescents’ social reasoning concerning the exclusion of an African-American child, Killen and colleagues (2002) interviewed European-American, African-American, Latino, and Asian-American students in fourth, seventh, and tenth grades. Students’ reasoning about explicit racial/ ethnic exclusion was multifaceted and contextual. Participants generally considered explicit racial/ethnic exclusion to be wrong for moral reasons, such as unfairness, and older children were more likely than younger children to use fairness reasoning when evaluating friendship decisions based on race/ethnicity. However, depending on the context, children and adolescents used personal choice and social–conventional reasons instead of moral ones. Specifically, children and adolescents were more likely to use personal choice reasoning when evaluating friendship decisions based on race/ethnicity than when evaluating decisions to exclude someone from a club or from a school solely because of

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their race/ethnicity (Killen et al., 2002; see also Phinney & Cobb, 1996). In addition, when the situation involved excluding someone from a club, some children and adolescents gave priority to social–conventional reasons, such as group functioning, over moral reasons (Killen et al., 2002). Concerning the indirect effect of stereotypes on children’s reasoning about exclusion, Killen and Stangor (2001) asked European-American students in first, fourth, and seventh grade to evaluate excluding children from counterstereotypical activities based on race/ethnicity or gender. The situations involving race/ethnicity were (1) excluding a European-American child from a basketball club and (2) excluding an African-American child from a math club. Most children and adolescents considered it wrong to exclude someone based solely on their race/ethnicity. However, when the situations were made more complex and participants had to pick either a European-American or an African-American to join the club, adolescents were more likely than children to use stereotypes to make the decision. In other words, adolescents would choose the African-American for the basketball club and the European-American for the math club. Adolescents were also more likely than children to justify their decision by saying it would improve group functioning. Stereotypes differ from prejudice in that most research with children operationally defines prejudice as the tendency to attribute negative characteristics to outgroup members (Aboud & Amato, 2001). This research has found that children are less likely to attribute negative characteristics to members of an outgroup as they get older (Aboud & Levy, 2000). However, other studies have found that children and adolescents still have negative racial/ethnic attitudes and prejudice, depending on the context. For instance, in one study, EuropeanAmerican sixth through tenth graders were more prejudiced than AfricanAmerican youth in the same grades when asked about intimate interracial interaction (i.e., dating and marriage), but not when asked about casual interracial interaction, such as that taking place in school or in restaurants (Moore, Hauck, & Denne, 1984). Research on children’s and adolescents’ social reasoning also finds that negative racial/ethnic attitudes vary based on context and on personal experience (Killen et al., 2006). In a study with college students, Killen et al. (2004) examined how students evaluated decisions to exclude others based on race/ethnicity from nonintimate relationships (voting for someone for student council and going to a baseball game with someone) and intimate relationships (dating). Students judged a decision not to vote for someone or go to a baseball game with an interracial group as wrong, basing their decision on discrimination and prejudice. However, refraining from dating someone of another race was evaluated more often as a personal reason, and less often as a moral transgression, due to the personal discretion associated with choices of romantic partners. Thus, children and adolescents view decisions about intimate social relationships mostly as a matter of personal choice.

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To determine where children and adolescents draw the line between viewing racial/ethnic exclusion as wrong or as a matter of personal choice, a multiracial/ethnic sample of fourth, seventh, and tenth graders was interviewed about multiple levels of intimate relationships (Killen et al., in press). Specifically, participants were asked about racial exclusion in a friendship context, a dating context, and a home context in which a student did not invite a cross-race friend over to his/her house for a sleepover party due to parental discomfort. Scenarios included multiple possible reasons (both race-based and non-race-based) for the exclusion. As with previous research, both majority and minority participants considered racebased exclusion in general as wrong. There were racial/ethnic differences, however, in evaluations of non-race-based exclusion from friendship, with minority participants more likely than majority participants to evaluate it as wrong. Similar to previous studies on race-based exclusion, adolescents were less likely than children to consider non-race-based exclusion from friendship wrong. With age, children rejected parental discomfort as a legitimate reason for a European-American child to refrain from bringing an African-American friend home for a sleepover party; conversely, with age, children condoned peer disapproval as a legitimate reason for refraining from bringing an African-American friend as a date to a dance. These findings point to ways in which nonmoral social considerations, such as parental discomfort, peer approval, and group functioning, are used by children, particularly majority children, to justify racial exclusion. What is not clear is the extent to which these considerations are proxies for stereotypic beliefs. For example, Levy, Chiu, and Hong (2006) have shown how children invoke lay theories about work ethics (“Protestant work ethic,” or social–conventional knowledge) to make decisions about the fair allocation of resources (moral decision making) based on race and ethnicity. Whether children are aware of the potential ways in which societal traditions, expectations, and group approval reflect underlying stereotypes or prejudicial behavior requires further research. Moreover, these findings provide further evidence for how contextual factors are differentially weighed by children and adolescents when evaluating racial/ethnic exclusion (Kelly et al., 2006). b. Bullying/Victimization. In its extreme, peer exclusion is a form of bullying or victimization. By definition, bullying/victimization involves an aggressive relationship between two or more people that is based on an imbalance of power (Espelage & Swearer, 2003; Graham & Juvonen, 2002; Olweus, 1994). Race/ethnicity may play an important role in bullying/victimization, and in particular in exclusion used to bully/victimize, for at least two reasons. First, the societal imbalance of power between race/ethnicities may contribute to the imbalance of power in bully/victim relationships (Graham & Juvonen, 2002). Second, bullies tend to pick on others who are different (Rubin et al., 2006), and race/ethnicity is one very visible difference between people. Despite these important potential connections, little research has examined the issue in depth.

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The research that has examined intergroup relations and bullying/victimization focuses on prevalence by race/ethnicity. For instance, Juvonen, Nishina, and Graham (2006) found that minority students enrolled in heterogeneous schools experience less bullying and harassment than when enrolled in racially imbalanced or racially isolated schools. One study of race/ethnicity and bullying attitudes found that Australian seventh through tenth grade ethnic majority (Anglo-Saxon) and ethnic minority (non-Anglo-Saxon) students differed in their attitudes toward bullying (Nguy & Hunt, 2004). Specifically, ethnic majority males were most likely to believe that bullying would result in positive outcomes (i.e., bullying makes you feel good about yourself; bullying prevents you from being bullied). Ethnic minority students placed more importance than ethnic majority students on these positive outcomes, but they did not believe that bullying would achieve them (Nguy & Hunt, 2004). Although the relation between bullying/victimization and social reasoning in intergroup contexts still needs to be examined, the relation between children’s experience with peer exclusion and social reasoning in intergroup contexts has been studied. Specifically, Margie et al. (2006) investigated how children’s and adolescents’ personal experiences of being excluded (both because of their race/ethnicity and for non-race/ethnicity-based reasons) are related to their moral judgments about exclusion in interracial peer contexts. Majority (European-American) and minority (African-American, Latino, Asian-American, and other non-European-American racial/ethnic groups) fourth, seventh, and tenth graders evaluated three potential reasons for exclusion (race, lack of common interest, and not fitting in with friends) from an interracial friendship situation. Personal experiences with exclusion were differentially related to evaluations of exclusion for majority and minority participants. Specifically, majority students’ evaluations of race-based exclusion did not differ based on their personal experience with peer exclusion. Minority students, however, who reported personal experiences with peer exclusion were more likely to evaluate race-based exclusion as wrong than were minority students who had not. Future research needs to delve into why personal experience with exclusion and reasoning about exclusion differ by minority/majority group status. 3. Schools and Communities Another factor that contributes to social exclusion is the racial/ethnic segregation of U.S. schools and communities. School and community segregation is an example of social exclusion at the societal level, in addition to creating an atmosphere of exclusion that influences children’s and adolescents’ perceptions and actions. In the latter half of the twentieth century in the United States, there was increasing awareness of racial inequality and the detrimental effects of segregation (Dovidio & Gaertner, 2004; Gaertner & Dovidio, 1986). This awareness was accompanied by an increase in racially/ethnically mixed schools and communities. However, toward the end of the twentieth century, the trend had reversed,

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with schools and communities becoming increasingly segregated by race (Frankenberg & Orfield, in press). This is especially true for EuropeanAmerican children and adolescents, as families move farther outside of cities and close-in suburbs of cities. For instance, in the 2000–2001 academic year, the average European-American public school student attended a school in which 80% of the students were also European-American, making European-American children the most segregated racial/ethnic group in American public schools. Attending more homogeneous schools and living in less diverse communities reduces the possibilities for intergroup contact and relationships, which are critical to the reduction of prejudice, discrimination, and social exclusion based on race/ethnicity. Intergroup contact plays a role in children’s biases and preferences for ingroup and outgroup members (Aboud, 2003; Brewer, 1999; Nesdale, in press; Nesdale et al., 2005; Rutland, 2004). For instance, Aboud (2003) found that 4- to 7-year-old children who attended a racially heterogeneous school did not exhibit positive ingroup and negative outgroup bias in a reciprocal way. In other words, preference for the ingroup did not equal dislike for the outgroup. However, 4- to 7-year-old children who attended a racially homogeneous school did exhibit positive ingroup and negative outgroup bias in a reciprocal way at times. Similarly, a set of studies with first and fourth graders found that, overall, European-American children in heterogeneous schools did not evidence racial/ethnic bias but European-American children in homogeneous schools did (McGlothlin & Killen, 2006; McGlothlin et al., 2005). Similarly, EuropeanAmerican students in homogeneous schools are more likely than EuropeanAmerican students in heterogeneous schools to use stereotypes to interpret racial/ethnic exclusion decisions (Kelly et al., 2006). Regardless of a school’s homogeneity or heterogeneity, children and adolescents can experience racial/ethnic exclusion in school due to the pressure to conform or not to conform to stereotypes (Aronson, Fried, & Good, 2002; Aronson & Steele, 2005; Steele, 1997). For instance, in academic situations in which the stereotype is that African-American students are not as intellectually capable as EuropeanAmerican students, African-American students perform significantly worse on tests than European-American students when they are told the exam is a test of their intellectual ability. In contrast, when told the purpose of the test is nonevaluative, African-American and European-American students perform equally well (Steele & Aronson, 1995). In other words, when stereotypes are activated, the pressure not to conform to the stereotype interferes with African-American students’ ability to perform at their best, thereby unintentionally “confirming” the stereotype (Aronson & Steele, 2005). This kind of pressure can lead to repeated poor performance in academic situations, which in turn can lead to the exclusion of qualified people from academic and professional opportunities (see Aronson & Steele, 2005, for a review of the extensive literature on stereotype threat).

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C. INCLUSION Racial/ethnic inclusion is fostered by healthy relationships between people of different races/ethnicities. Therefore, we review literature on aspects of development that promote healthy relationships between people of different races/ethnicities: ethnic identity, racial socialization, and cross-race relationships. 1. Ethnic Identity Ethnic identity is the part of one’s identity associated with membership in a particular racial/ethnic group (Greig, 2003; Quintana, Castaneda-English, & Ybarra, 1999). Ethnic identity theory proposes that ethnic identity exploration results in positive attitudes and a sense of belonging to the ingroup (Cross, 1991; Phinney, 1990). Ethnic identity development is proposed to occur through three stages: (1) diffusion/foreclosure (before exploration of ethnicity), (2) moratorium (during exploration of ethnicity), and (3) ethnic identity achieved (after exploration of ethnicity, committed to an ethnic identity) (Phinney, 1989). These stages appear to be more applicable to adolescents from racial/ethnic minority groups than to European-American adolescents (Phinney, 1989). In addition, adolescents from minority and majority groups differ in their focus when talking about ethnic identity. Specifically, in one study European-American adolescents were more likely to talk about ingroup/outgroup relations, while African-American adolescents were more likely to talk about the ingroup (Phinney & Tarver, 1988). Ethnic identity is related to a range of positive aspects of child and adolescent development, such as improved coping abilities, greater self-competence in academics, less depression and loneliness, and higher self-esteem, for both majority and minority group members (Davey et al., 2003; Greig, 2003; Phinney, 1989; Roberts et al., 1999). Other studies have found that higher selfesteem is associated with healthier reactions to racial/ethnic discrimination. For instance, adolescents who reported higher levels of self-esteem were less likely to become upset when experiencing peer and academic discrimination (Fisher et al., 2000). In addition, when faced with stereotypes and discrimination, African-American, Japanese-American, and Mexican-American adolescents with higher levels of self-esteem used proactive coping styles, while those with lower levels of self-esteem responded with verbal retorts (Phinney & Chavira, 1995). Because of its relation to self-esteem and to more positive adjustment (DuBois et al., 2002; Phinney, 1990), ethnic identity may encourage social inclusion and/or buffer children and adolescents from the negative effects of experiencing racial/ethnic exclusion and help them cope in more positive ways. The impact of ethnic identity on children’s moral reasoning about racial/ethnic exclusion has not been examined to date. Future research needs to address this topic. We hypothesize that children who have a strong ethnic identity may be

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more likely to judge exclusion based on race/ethnicity as wrong and may be more likely to use moral reasons than would children who have less developed ethnic identities and may explain exclusion in social–conventional or stereotypic terms. 2. Family Context: Racial Socialization Racial socialization is generally defined as parents’ communications to their children about race (Hughes & Chen, 1997; Johnson, 2001; Phinney & Chavira, 1995; Stevenson, 1995). Although all parents socialize their children, parents from minority racial/ethnic groups often include in their children’s socialization a focus on their minority group’s status within the larger society (Phinney & Chavira, 1995), including their group’s status within the larger societal system and negative images that society holds of their group. As with all kinds of socialization, parents’ goal is to help their children learn to function in society in productive and adaptive ways (Barnes, 1980; Boykin & Toms, 1985; Spencer, 1983). Some of the strategies that parents use to help racially/ethnically socialize their children are (1) promoting their ethnic group’s cultural history, customs, and values, which is thought to help children cope with negative messages they receive about their ethnic group, including prejudice and discrimination; (2) making their children aware of what it means to be a minority and how this will impact how they function in society; and (3) promoting the goals and values of the majority society (Barnes, 1980; Boykin & Toms, 1985; Hughes & Chen, 1997). Modern conceptualizations of these socialization strategies also examined parents’ promotion of mistrust of the outgroup (Hughes & Chen, 1997). Studies including African-Americans, Mexican-Americans, and JapaneseAmericans have found that most parents racially/ethnically socialize their children (Biafora et al., 1993; Branch & Newcombe, 1986; Marshall, 1995; Phinney & Chavira, 1995; Sanders Thompson, 1994; Thornton et al., 1990). What parents say to their children can vary widely (Sanders Thompson, 1994), but parents have reported discussing their ethnic group’s cultural history and values more often than preparing their children for prejudice and bias they might encounter (Hughes, 2003). Ethnic differences in what parents say have also been found. In particular, AfricanAmerican parents tend to discuss prejudice more often than Mexican-American or Japanese-American parents, and Japanese-American and African-American parents report emphasizing adaptation to society more often than Mexican-American parents (Phinney & Chavira, 1995). As children reach middle childhood and, especially, adolescence, parents’ discussions of racial issues with their children increase (Knight, Cota, & Bernal, 1993; Marshall, 1995; Spencer, 1983). Parents’ racial socialization practices vary, based on their socioeconomic background, attitudes, and personal experiences (Hughes & Johnson, 2001). For instance, parents are more likely to pass on messages about race to their children that they received from their parents (Hughes & Chen, 1997). Parents who report experiencing bias at their jobs are more likely to discuss issues of discrimination

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with their children and more likely to promote racial mistrust (Hughes & Chen, 1997). Middle-class African-American parents restrict their adolescents’ autonomy more often than do European-American parents, due to their concerns about protecting their children from experiences of discrimination and victimization (Smetana, 2000; Smetana & Gaines, 1999). In general, racial socialization, such as teaching about racial/ethnic heritage and clear expectations for children’s participation in cultural activities, is associated with positive outcomes for children and adolescents. For instance, AfricanAmerican and Chinese-American children who are racially socialized by their parents have more positive ingroup attitudes than those children who are not racially socialized (Barnes, 1980; Ou & McAdoo, 1993; Spencer, 1983). African-American children, Jewish adolescents, and Mexican-American adolescents whose parents discussed race/ethnicity as part of their parenting practices evidence more developed ethnic identities (Davey et al., 2003; Knight et al., 1993; Marshall, 1995; Quintana et al., 1999). Children whose parents highlight their ethnic group’s culture and history tend to have higher levels of self-esteem and more knowledge about their ethnic group (Marshall, 1995; Stevenson, 1995). Although children whose parents overemphasize possible racial/ethnic barriers tend to report lower self-efficacy and distrust of mainstream society (Biafora et al., 1993; Marshall, 1995; Ogbu, 1974), children whose parents prepare them for bias in society are less likely to be depressed (Stevenson et al., 1997) and more likely to have higher grades and higher self-esteem (Bowman & Howard, 1985). As noted previously, higher levels of ethnic identity and self-esteem are related to less victimization and more positive adjustment in general, which contribute to healthy relationships between people of different races/ethnicities, such as cross-race friendships. 3. Peer Context: Cross-race Friendship Studies of friendship in general have found that perceived similarity between friends is important for the establishment and maintenance of friendships and that friends tend to be similar in gender, ethnicity, and age (Rubin, Bukowski, & Parker, 1998). However, racially prejudiced attitudes do not appear to be a strong indicator of children’s choice of friends. In a sample of first through sixth grade students, Aboud and her colleagues (2003) found that European-American children with higher prejudice scores had equal numbers of same- and crossethnic friends, but their cross-ethnic friendships were lower on quality overall. However, prejudice scores and cross-ethnic friendships for African-American students were not related. Another factor that likely plays a role is similar interest in activities. A set of studies found that, in general, children judged similarity of activities (i.e., soccer, basketball) more important than race when making decisions about friendship (Margie et al., 2005; McGlothlin & Killen, 2006; McGlothlin et al., 2005). In addition, Hamm (2000) found that cross-ethnic adolescent friends were more similar in their substance use than same-ethnic friends.

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Concerning the racial/ethnic composition of cross-race friendships, Quillian and Campbell (2003) found that Hispanic adolescents were most likely to prefer friends from the racial group they identified with. In other words, when they had cross-race friendships, White Hispanic adolescents were most likely to have EuropeanAmerican friends, whereas Black Hispanic adolescents were most likely to prefer friends who were African-American. Similarly, when they had cross-race friends, European-Americans were most likely to choose White Hispanic students as friends, but African-Americans were most likely to choose Black Hispanic students as friends (Quillian & Campbell, 2003). Asian-American adolescents were most likely to choose White Hispanic adolescents as cross-race friends. School environments can directly bear on the rate and occurrence of crossrace friendships. School administrators can encourage cross-ethnic interaction and friendship by ensuring that classrooms and extracurricular activities are integrated and by evenly dividing ethnicities across academic and nonacademic tracks (Hallinan & Smith, 1985; Moody, 2001; Tropp & Prenovost, in press). Another way schools can promote cross-race friendship is by limiting crossgrade contact, because students who interact only with students in the same grade are more likely to have cross-race friends than students who interact with children in other grades (Moody, 2001). Teachers can also influence cross-ethnic friendship. For instance, Hallinan and Teixeira (1987) found that reducing emphasis in the classroom on academic status by using cooperative learning instead of accentuating standardized tests and grades increases the likelihood that European-Americans will choose African-Americans as friends. It is important to promote cross-race friendship, because intergroup contact under the proper circumstances can reduce prejudice and diminish experiences of racial exclusion (Allport, 1954; Pettigrew & Tropp, 2000). Gaernter and Dovidio (2000) have proposed the common ingroup identity model to promote positive friendships and relationships among children from different racial and ethnic backgrounds. This model involves enabling children to identify with a common group identity that is distinct from race and ethnicity (such as the school identity or a team identity) and promotes a sense of belonging to a group that has shared interests and beliefs. Interventions with this model have successfully reduced prejudice and racial biases, as well as promoting cross-race friendships.

IV. Conclusion Children experience exclusion as a function of gender and race/ethnicity at a young age and these experiences continue throughout life. How children understand these experiences, how such experiences contribute to children’s healthy social development, and the ways in which such experiences are related to adult forms of

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prejudice and discrimination, as well as judgments about fairness and justice, lie at the heart of developmental intergroup research on inclusion and exclusion. On the one hand, the experience of exclusion may lead some children to be ostracized, withdrawn, and rejected. On the other hand, this type of experience can lead other children to be empathic and to judge exclusion as wrong from a moral viewpoint. After all, research has shown that concepts of justice and fairness emerge out of the early peer conflict experiences with toys and desired objects; reciprocity stems from the give-and-take negotiation that takes place between young children regarding sharing toys and taking turns (Killen, 1991; Smetana, 1995). Thus, for some children, the experience of peer conflict over toys provides an essential experience for understanding what makes it wrong to take someone else’s toy. Yet, for other children, repeated experiences as a victim contribute negatively toward their own development by hindering their development of social competence. Piaget (1932) theorized that children’s social exchanges regarding sharing toys and turn-taking provided the social experience necessary to develop a sense of fairness (i.e., to the extent that my friend and I both want the same toy we have to share it). Understanding the concept of fair distribution of resources requires discovering that other people sometimes want the same things that we want. In these terms, and according to Piaget (1932), peer conflict facilitates change. Through conflict, the child becomes aware of the other person’s perspective and, by reciprocity, understands that fairness is a necessity in social interactions. In moral development, this sequence of events is referred to as the experiential basis necessary for understanding the Golden Rule or, as theorized in philosophy, Kant’s categorical imperative (i.e., act in such a way that you would will your act to be universal; Turiel, 1983). Similarly, we propose that understanding the wrongfulness of prejudice, discrimination, and the use of stereotypes stems from children’s exclusion experiences in social groups. Being excluded because of a person’s group membership enables someone to understand what it feels like to be excluded and, under the right conditions, to develop the moral judgments involved with evaluating exclusion from social groups. As researchers in the area of peer relationships have shown, however, too much exclusion experience can lead to social maladjustment, loneliness, and anxiety. Similarly, too much conflict about sharing toys can lead to aggressive and negative exchanges among peers (or to the acceptance of retaliation and retribution as legitimate forms of interaction). Thus, we are not proposing that exclusion in and of itself is a positive aspect of development. Clearly, children who experience extreme exclusion are at risk for a host of negative social behaviors and dispositions. Yet, some experience may provide a basis for empathy about what makes it wrong and a sense of what is unfair. Thus, in many studies, we find that girls and children from minority racial/ethnic groups are more likely than boys or children from majority racial/ethnic groups to judge that exclusion based on group membership is wrong. Their reasons

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regarding what makes exclusion based on group membership as wrong include the wrongfulness of discrimination and prejudice, both complex concepts in the moral domain. Understanding when these experiences are adaptive or maladaptive remains to be better understood. Furthermore, we propose that exclusion based on group membership is psychologically more complicated than what is required when children develop an understanding that not sharing toys is unfair. This is because exclusion involves understanding intergroup relationships and understanding what it means to be a member of an ingroup or an outgroup. Psychologically, this involves issues of social categorization and social identity (Abrams et al., 2005; Rutland, 2004), as well as understanding what it means to treat others differently solely because of group membership. Treating someone in an unfair way in terms of denying them resources (or toys) may be more straightforward for children (and adults) to conceptualize as wrong than treating someone in an unfair way in terms of prejudice. In this chapter, we documented the range of children’s experiences with exclusion and the types of intergroup judgments and attitudes that emerge during childhood. Research on intergroup contact comes closest to providing evidence for the relation between experiences and judgments about exclusion, and fortunately, this has become a robust area of empirical research in childhood, as described briefly in this chapter (Tropp & Prenovost, in press). We reviewed research on gender and racial/ethnic exclusion in childhood. In doing so, we became increasingly aware of the gaps in these two areas of research. Although there are commonalities in the forms that exclusion takes across group membership categories, such that both forms of exclusion are evaluated as wrong on the basis of discrimination against a member of a group, there are also clear differences in that many societies explicitly condone certain forms of gender exclusion (e.g., same-sex schools, boy scouts, sports) but refrain from supporting racial exclusion. Even more limiting are the differences in the questions that researchers address, which leave gaps when comparing these two bodies of knowledge. For example, contact between children from different racial and ethnic groups has been examined extensively in the United States, United Kingdom, and Europe. This is due to the changing patterns of schooling in the United States, which began as laws that went into effect to integrate schools, and to changing immigration patterns in the United Kingdom and Europe. Cross-gender interactions, however, have rarely been compared with same-gender interactions; nor have researchers proposed what types of outcomes may exist regarding such comparison (for an exception, see Brown & Bigler, 2005). Some might argue that cross-gender interaction is not a relevant phenomenon to examine because children grow up, for the most part, in gender-integrated households and attend gender-integrated schools. Yet, as Eagly and Diekman

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(2005) have noted, many segments of society are not gender integrated, and this lack of experience with gender-integrated settings has perpetuated exclusion of females from various opportunities (political office; math, science, and engineering fields; professional sports, Wall Street). And, in fact, developmental researchers have documented gender-segregated playgrounds and play activities and high levels of gender-specific messages that remain in place throughout much of current society in many countries. Thus, research on the effects of intergroup contact on attitudes about gender exclusion is a relatively unexplored but a much needed area of research. Moreover, in most of the studies reviewed on social reasoning about exclusion based on group membership, children and adolescents judged it more legitimate to exclude girls than boys from peer activities (see Figure 2). As shown in Figure 2, children gave more moral reasons for why racial exclusion was wrong than why gender exclusion was wrong when interviewed about peer group exclusion (the identical scenario was used, with one version being about gender and the second about racial exclusion) (see Killen et al., 2002). An exception to this pattern lies with cross-gender stereotypic activities, in which it is more acceptable for a girl to engage in boy-type play (e.g., baseball) than for a boy to engage in girl-type play (e.g., ballet). This may be due to the notion that it is more acceptable to move up rather than down the social

0.9 0.8

Moral Social Con

Proportion of Reasons

0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 Gender Race Target of Exclusion Fig. 2. Proportion of moral and social–conventional reasons for gender and racial targets of exclusion in a peer group context (source: Killen et al., 2002).

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status hierarchy (Horn, 2003; Turiel, 2002). Nonetheless, there are clearly differences in how gender exclusion and racial/ethnic exclusion are evaluated and when children believe it is legitimate to exclude based on group membership. At the same time that gender exclusion is more often condoned than racial exclusion, stereotypes and biases about race/ethnicity are typically more negative than those about gender. Furthermore, although boys and girls eventually become intimate and romantic partners as young men and women (for the most part), children from different ethnic backgrounds become less intimate as they get older, to the point at which cross-ethnic and interracial marriage remains exceedingly rare (Kennedy, 2003). Thus, this increasingly segregated social world in the area of ethnicity becomes an obstacle for positive intergroup relationships and attitudes. Direct contact with others provides the necessary experience to challenge and contest negative stereotypes that permeate the culture. When direct contact is absent, the work needed to overcome stereotypes and biases becomes that much greater. Extended contact and indirect contact in the form of knowing another individual who has cross-race friends can provide a partial answer but this form of contact is not a substitute for positive direct contact (Cameron, Rutland, & Brown, in press). With schools in the United States becoming increasingly segregated at the end of the twentieth century, much work remains to provide children with opportunities to be inclusive toward others from different ethnic backgrounds (Frankenberg & Orfield, in press). What does a social reasoning perspective provide? We begin by reiterating our social–cognitive theoretical perspective that understanding social attitudes, motives, judgments, and interpretations of social exchanges is necessary to understand social behavior. Observing behavior tells what people do but not why they did it. Without the “why?” we have little basis to judge the merits of the behavior from a moral viewpoint. Social information processing has provided muchneeded knowledge on, for instance, how children attribute motives to others’ behavior and how the attribution of motives reveals children’s social skills (and social deficits). Children who overattribute hostile intention, for example, are more likely to be aggressive and antisocial toward others. This aggressive reaction often leads to social rejection from peers and puts them at risk for negative social development. Thus, how children read social cues is important (Arsenio & Lemerise, 2004). We take this to the next step and argue that how children explain, evaluate, and reason about others’ actions is also revealing of their likelihood to perform similar actions. Do children believe that it is acceptable to exclude someone from a group just because of their gender or race/ethnicity, and why? What is the basis for exclusion judgments? This evaluative perspective leads us to understand the basis of children’s moral, social–conventional, and psychological orientations toward exclusion. What makes exclusion psychologically complex? We argue that it has to do, in part, with the multiple forms of reasoning brought to bear on evaluations of

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exclusion. For example, when Tiger Woods, the world-famous golf player who is part African, part Asian, and part European, was asked to explain why he would play at Augusta National, a U.S. golf club that excludes women and hosts the Masters Tournament, when not too long ago he would have been excluded for his race/ethnicity, he responded: “Augusta National is entitled to set up their own rules the way they want them” (social–conventional reasons). Upon further probing by reporters, Woods stated: “It’s their prerogative to set it up that way” (NY Post) (personal choice reasons). “Would I like to see women members?” he (Tiger Woods) asked. “Yes, that would be great but I am only one voice. I’m not even a regular member” (inclusion judgment). “Is it unfair? Yes. Do I want to see a female member? Yes. I realize that it’s discrimination and it’s wrong” (moral). “I’d like to have a chance to win the Masters’ three years in a row” (personal priority over the wrongfulness of exclusion). These quotations from Tiger Woods are excerpts from different reporters’ queries and do not constitute an in-depth interview with systematic probes and assessments. Nonetheless, they demonstrate how an individual’s evaluation of exclusion changes as his or her judgment changes. Woods began by explaining gender exclusion as a social–conventional issue (“It’s how it’s always been done.”). He brought in personal prerogative reasons and, after further probing, acknowledged the moral dimension, that is, the unfairness that results from discrimination. Reflection and evaluation may, in fact, serve to enable an individual to rethink and reconsider their decision to exclude or include. In childhood, we believe that this is part of the child’s everyday experience. Each day, children are confronted with different types of exclusion experiences and their reflection and reasoning about it push them toward a different understanding about the phenomenon, particularly as their social cognitive reasoning changes from early childhood to late adolescence. Through detailed analyses of children’s experiences with exclusion based on group membership, and their reasoning about it, we can better understand the development of intergroup attitudes and the precursors to adult forms of prejudice and stereotypes as well as justice and fairness.

Acknowledgments The work described in this chapter was supported, in part, by a grant from the National Institute of Child Health and Human Development (1R01HD04121). We thank the doctoral students at the University of Maryland (Alaina Brenick, Alexandra Henning, Noah Jampol, Megan Clark Kelly, and Cameron Richardson) and our research colleagues (David Crystal, Christina Edmonds, Jennie Lee-Kim, Heidi McGlothlin, Yoonjung Park, and Martin Ruck) for their collaboration on the research described in this paper. Thanks are also extended to Rasha Dalbah and Brian Panek for technical assistance with the manuscript.

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Steele, C. M., & Aronson, J. (1995). Stereotype threat and the intellectual test performance of African-Americans. Journal of Personality and Social Psychology, 69, 797–811. Stevenson, H. C. (1995). Relationships of adolescent perceptions of racial socialization to racial identity. Journal of Black Psychology, 21, 49–70. Stevenson, H. C., Reed, J., Bodison, P., & Bishop, A. (1997). Racism stress management: Racial socialization beliefs and the experience of depression and anger in African American youth. Youth and Society, 29, 172–222. Stoddart, T., & Turiel, E. (1985). Children’s concepts of cross-gender activities. Child Development, 56, 1241–1252. Szalacha, L. A., Erkut, S., Garcia-Coll, C., Alarcon, O., Fields, J. P., & Ceder, I. (2003). Discrimination and Puerto Rican children’s and adolescents’ mental health. Cultural Diversity and Ethnic Minority Psychology, 9, 141–155. Tajfel, H., & Turner, J. C. (1979). An integrative theory of intergroup conflict. In W. G. Austin & S. Worchel (Eds.), The social psychology of intergroup relations (pp. 33–47). Monterey, CA: Brooks-Cole. Taylor, J., & Turner, R. J. (2002). Perceived discrimination, social stress and depression in the transition to adulthood: Racial contrasts. Social Psychology Quarterly, 65, 213–225. Theimer, C. E., Killen, M., & Stangor, C. (2001). Young children’s evaluations of exclusion in gender-stereotypic peer contexts. Developmental Psychology, 37, 18–27. Theimer-Schuette, C. (2000). Children’s evaluations of gender roles in a home context. Unpublished dissertation, University of Maryland. Thornton, M. C., Chatters, L. M., Taylor, R. J., & Allen, W. R. (1990). Sociodemographic and environmental correlates of racial socialization by Black parents. Child Development, 61, 401–409. Tropp, L., & Prenovost, M. (in press). The role of intergroup contact in predicting children’s interethnic attitudes: Evidence from meta-analytic and field studies. In S. Levy & M. Killen (Eds.), Intergroup relations: An integrative developmental and social psychological perspective. Oxford: Oxford University Press. Turiel, E. (1983). The development of social knowledge: Morality and convention. Cambridge, England: Cambridge University Press. Turiel, E. (1998). The development of morality. In W. Damon (Ed.), Handbook of child psychology (5th ed., Vol. 3: Social, emotional, and personality development, pp. 863–932). New York: Wiley. Turiel, E. (2002). Culture and morality. Cambridge, England: Cambridge University Press. Turiel, E. (2006). Thought, emotions, and social interactional processes in moral development. In M. Killen & J. G. Smetana (Eds.), Handbook of moral development (pp. 7–35). Mahwah, NJ: Lawrence Erlbaum Associates. Verkuyten, M., & Thijs, J. (2002). Racist victimization among children in the Netherlands: The effect of ethnic group and school. Ethnic and Racial Studies, 25, 310–331. Wainryb, C. (2006). Moral development in culture: Diversity, tolerance, and justice. In M. Killen & J. G. Smetana (Eds), Handbook of moral development (pp. 211–242). Mahwah, NJ: Lawrence Erlbaum Associates. Wigfield, A., & Eccles, J. S. (2002). Students’ motivation during the middle school years. In J. Aronson (Ed.), Improving academic achievement: Impact of psychological factors on education (pp. 159–184). San Diego, CA: Academic Press. Wigfield, A., Eccles, J., Schiefele, U., Roeser, R., & Davis-Kean, P. (2006). Development of achievement motivation. In N. Eisenberg (Ed.), Handbook of child psychology (6th ed., Vol. 3, pp. 933–1002). New York: Wiley & Sons, Inc. Williams, J. C., & Cooper, H. C. (2004). The public policy of motherhood. Journal of Social Issues, 60, 849–865. Wittig, M., & Molina, L. (2000). Moderators and mediators of prejudice reduction in multicultural education. In S. Oskamp (Ed.), Reducing prejudice and discrimination (pp. 295–318). Mahwah, NJ: Lawrence Erlbaum Associates.

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WORKING MEMORY AS THE INTERFACE BETWEEN PROCESSING AND RETENTION: A DEVELOPMENTAL PERSPECTIVE

John N. Towsea, Graham J. Hitchb, and Neil Hortona a

DEPARTMENT OF PSYCHOLOGY, LANCASTER UNIVERSITY, BAILRIGG, LANCASTER LA1 4YF, UNITED KINGDOM b DEPARTMENT OF PSYCHOLOGY, UNIVERSITY OF YORK, YORK Y010 5DD, UNITED KINGDOM

I. II.

INTRODUCTION THE CONCEPT OF WORKING MEMORY

III.

THE DEVELOPMENT OF WORKING MEMORY

IV.

EXPLAINING COMPLEX SPAN IN CHILDREN A. EXTENDING OUR UNDERSTANDING OF THE ENDURANCE OF WORKING MEMORY B. BEYOND THE SIMPLE TASK-SWITCHING MODEL

V.

TAKING DEVELOPMENTAL QUESTIONS ABOUT WORKING MEMORY SERIOUSLY

VI. THEORIES OF WORKING MEMORY IN CHILDREN: AN INTEGRATION VII. CONCLUSION ACKNOWLEDGMENT REFERENCES

I. Introduction Picture a child at her seat in her primary school class. She is trying to figure out an arithmetic calculation written on the class board. It reads 27 16⫹ The child quickly recognizes the type of arithmetic task before her and begins by thinking “7 plus 6, that is 13 … so I need to put the 3 down on the right below the 6 and carry 1 … so now I have done the units, I can move to the next column and add up the numbers. There is 2 and there is 1 so that makes 3 so I put 3 down … and the answer is 33.” Seemingly the child was aware of what to do with carries in addition, but when it came to the point at which the carry was relevant, she forgot to use that information and consequently generated the incorrect answer. 219 Advances in Child Development and Behavior R.V. Kail : Editor

Copyright © 2007 Elsevier Inc. All rights reserved.

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Mental arithmetic is an example of when transient memories are necessary for the successful retention of the partial products of thoughts. Mistakes of memory— whether in this example or from related computational procedures in numerical calculations—can and do occur (e.g., Hitch, 1978). They illustrate the deployment of working memory in everyday cognitive tasks, and it is the attempt to review and understand what we know about working memory and its development that is central to the current chapter. Consider an alternative vignette. A teacher has carried out her lesson in which children have been assigned to a variety of tasks, all of which involve observation of the room around them and manipulation of it. The teacher senses that the lesson should draw to a close and addresses a child who is looking at some potted plants nearby. “George, please can you stop counting up the leaves on the plant now. Pick up the water jug and carefully finish watering the plants; please try not to spill too much water! Then put the jug back on the shelf and put your observation book away in the red cupboard. When you have finished that come and sit down at the front of the class so that we can all talk about what we have been doing.” The teacher than directs her attention to other children and the tasks they need to do so as to tidy up. A few minutes later, with all the children gathered together, the teacher looks around the class and notices that it is not as tidy as she would like. She realizes for example, that George’s observation book is still lying open on the table next to the plants, and some other children have not entirely carried out their instructions either. The teacher may not be terribly pleased to discover that the children fell short of complying with her requests. Even though she probably does not infer that the class was being deliberately mischievous or disobedient, she may feel a little exasperated. What the teacher or an observer may not fully appreciate, though, is the extent to which working memory constraints may play a substantial role in the children’s ability to carry out a set of instructions. While the teacher may view the tasks as parts of a routine script (tidy up and put things away before the end of class), children may not recognize this in the same way and instead may envisage the tasks as being independent and unrelated. Moreover, in completing one task—watering the plants and putting the jug away—the child is prone to forget subsequent instructions. Working memory function can be an important predictor of classroom behavior as well as scholastic achievement (Gathercole & Alloway, in press). This serves as a further indication of the relevance of understanding the theoretical concept of working memory and its development. In this chapter we discuss the concept and measurement of working memory as a limited capacity system, with particular reference to school-aged children. We discuss the commonly held view, whether explicit or implicit, that working memory capacity corresponds to the size of a pool of resources that can be shared between central processing operations and retention functions. We argue that this interpretation is insufficient and we discuss evidence suggesting that working

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memory is also limited by the rate at which it loses transient information. We then show it is possible to measure the period over which information can be maintained in an active state in working memory and we describe a simple “taskswitching” account of working memory capacity. We discuss subsequent research that confirms the importance of taking into account the dynamics of forgetting in working memory, while at the same time illustrating the incompleteness of the task-switching account. This leads us to outline how one might begin to integrate insights from different research programs into a common framework.

II. The Concept of Working Memory Working memory has been studied both as a research construct in its own right (Baddeley & Hitch, 1974; Baddeley, 1986; Halliday & Hitch, 1988) and as a central capacity that relates to a wide range of cognitive skills and traits in adults (Colom et al., 2004; Kane & Engle, 2003; Kyllonen & Christal, 1990) and children (Bayliss et al., 2003; Hitch, Towse, & Hutton, 2001; Swanson & Berninger, 1995). However, there are subtle differences in how the concept of working memory has been used and measured, and these differences can lead to confusion. To be clear, therefore, we set out our understanding of what working memory involves. We refer to working memory as the system that enables (internal or external) stimuli to be remembered over short periods of time and through which temporary representations are not only maintained, but also transformed and manipulated. Most contemporary approaches to working memory can be traced back to the theoretical framework offered by Baddeley and Hitch (1974), who suggested that immediate memory for verbal materials could be thought of as the result of a general-purpose executive system interacting with a slave store and that these resources underpin broader cognitive processes of reasoning, comprehension, and learning. Baddeley and Hitch (1974) explored some of the parameters of working memory through a program of interrelated experiments. However, ideas for the specific architecture of the working memory system emerged from subsequent work as much as from the original data. This development coalesced into its largely modern form when Baddeley (1986) suggested that working memory could be thought of as the product of three partially autonomous but interacting systems; the phonological loop, the visuospatial sketchpad, and the central executive. The central executive is the core engine of working memory but has turned out to be both controversial and difficult to analyze (Baddeley, 1996; Parkin, 1998; Towse & Houston-Price, 2001a). Baddeley and Hitch (1974) originally assumed the executive consisted of a limited capacity pool of general-purpose resources that could be allocated to different functions, principally those of temporary storage

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and information processing. Resources allocated to different executive functions were assumed to trade off against one another, such that when more resources are devoted to one activity, fewer are available for others. However, given difficulties in demonstrating such a trade-off, Baddeley (1986) proposed a different formulation, drawing upon the concept of a “supervisory attentional system” from Norman and Shallice (1986), that is, a limited capacity attentional system with little or no direct memory function (see also Baddeley, 1993; Baddeley & Logie, 1999). Subsequent work led to an attempted fractionation in which the executive controls a number of different functions such as dividing, focusing, and sustaining attention (see Baddeley & Della Sala, 1996; Baddeley et al., 1998). The phonological loop is a modality-specific buffer that retains verbally coded material. It is assumed to comprise a phonological store that can be refreshed by articulatory activity such as rehearsal (but see Jones, Macken, & Nicholls, 2004). This system is assumed to be responsible for the well-established effects of word length, phonological similarity, and articulatory suppression in immediate memory (or short-term memory, STM) tasks. Digit span and nonword repetition are examples of specific tasks appropriate for young children that are assumed to place demands on the phonological loop (Gathercole & Adams, 1993). The visuospatial sketch pad (VSSP; see also Logie, 1986) is a second modality-specific buffer designed to retain visual input (in a nonsensory, perceptually organized code; see Walker et al., 1997). The VSSP also assists in visual imagery, as in the example of mental synthesis in which participants are asked to imagine arranging basic shapes in novel configurations so as to produce new objects (Pearson & Logie, 2000). It has been proposed that VSSP involves the dissociable components of a visual buffer, inner scribe, and visual cache (see Pearson, 2001). While the visual buffer holds visual images that are available to conscious awareness and come from perceptual input, the inner scribe and the visual cache draw on activated long-term memory representations. The former element supports retention of color and form, and the latter supports the representation of dynamic information such as movement, as well as rehearsal and translation mechanisms. The fractionation of the VSSP reflects the different sorts of memorial codes that are necessarily handled by this system. Paradigms such as Corsi blocks and visual pattern span have often been used to load the VSSP (see Gathercole, 1999). Subsequently, Baddeley (2000) attempted to enhance the explanatory power of the working memory model by proposing a fourth component of the system: the episodic buffer (see also discussions in Andrade, 2001). One key feature of this component is that it is designed to act as a multimodal, integrative system capable of drawing upon representations from slave systems to form a coherent episodic record of an event or sequence of events. Being very much the youngest offspring of the working memory family, the episodic buffer has not been tested or specified to the same extent as the other components. Nonetheless, it is

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closely linked to the central executive, especially insofar as it receives input from other slave systems and long-term knowledge. In some ways, it represents a return to the notion of Baddeley and Hitch (1974) of a more general-purpose temporary memory device, although the episodic buffer separates memory and attentional functions, the latter being ascribed to the executive. The working memory model has been extraordinarily successful in terms of the breadth and extent of its impact and its longevity. Very few cognitive models have enjoyed the same staying power, and because the model has been so widely used and applied, one can certainly generate a strong claim that it has been thoroughly “road tested.” Perhaps contributing to its success is that it has been productively used at two rather different levels: as a particular model describing the architecture of those systems involved in immediate retention (which Baddeley, 1986, refers to as WMS, the specific details of the model) and as a more general framework or concept by which memory is seen as an active process that contributes to—indeed, is often integral to—ongoing cognition (which Baddeley, 1986, refers to as WMG, the general framework or concept of working memory). On the one hand, studies that explore WMS, and investigate the functioning of the phonological loop and/or visuospatial sketchpad, usually focus on STM paradigms, in which retention is very much the dominant requirement. On the other hand, studies that address WMG more commonly involve working memory span (described subsequently), in which the focus is on the combined processing and memory requirement. At the core of the specific model of working memory is the proposition that memory involves a set of modality-specific representations. A large body of empirical work has been assimilated to the model with respect to this idea; for a comprehensive account see, for example, Baddeley (1986, in press). The crux of this position, however, is that verbal information is held and manipulated separately—and quite possibly differently—from visuospatial information. This view is consistent with evidence already presented that the slave systems operate under different constraints, and it is also supported by both experimental and neuropsychological evidence that there are dissociations in representations according to the modality of input (Baddeley et al., 1975; De Renzi & Nichelli, 1975). As a result of this partitioning of the working memory model according to the modality of representations, slave systems have both common and unique properties. For example, there are the representations themselves and the relevant processes that maintain them in an active state (for example, by rehearsal). There are the cognitive operations that lead to transformation or manipulation of information, as well as translation into codes for other modalities. The distinction between “active” and “passive” memory codes has been important for the more precise specification of the phonological loop that handles verbal memory (in the form of the phonological store and the articulatory control process) and

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likewise for the VSSP in its handling of visual and spatial information (e.g., see Pickering, Gathercole, Hall & Lloyd (2001); Cornoldi & Vecchi, 2003, who distinguish memory for static or fixed stimuli from that for a dynamic or changing series of stimuli). As a consequence, understanding the functioning of WMS involves an appreciation of the details of each slave system, as they are not simply mirrors of each other in different modalities. The perspective from WMG, that working memory is a limited-capacity arena within which both processing and memory functions are carried out, leads to the corollary that these two functions compete against each other, such that there is a trade-off between processing and memory activities. This concept has fed considerable interest in experimental tasks that assess the ability to combine both functions. To this end Daneman and Carpenter (1980) developed reading span and listening span tasks. Reading span involved a sequence of unrelated sentences, each of which was read for meaning and where the sentence-final word was to be committed to memory for later, ordered recall. Listening span was the oral equivalent of reading span. These working memory span or “complex span” tasks, along with others (Turner & Engle, 1989; Shah & Miyake, 1996), share a common format. They comprise a sequence of processing episodes, each producing or being followed by an item to be recalled immediately after completing the final episode. Span represents the largest sequence of items that can be processed with successful retention of the products of processing. Daneman and Carpenter (1980) were the first to show that working memory span is strongly associated with linguistic skills. For example, they reported a correlation of 0.90 between reading span and the ability to link an anaphoric pronoun correctly to a preceding agent. Conventional measures of STM such as digit span are less strongly associated with linguistic abilities, arguably because they assess storage only, in the absence of any concurrent processing requirement (see also Daneman & Merikle, 1986, for a meta-analysis of the link between working memory span and cognitive abilities; for a discussion of alternative explanations for such phenomena, see Cowan, 2005). Daneman and Carpenter’s (1980) theoretical interpretation was that working memory span reflects the amount of workspace available for storage in combination with processing. It is worth noting that, common to a focus of many North American researchers, Daneman and Carpenter (1980) assumed that working memory acts as a single workspace. In contrast, what initially developed as a greater focus among European research was the multicomponent working memory model proposed by Baddeley and Hitch (1974) wherein the workspace corresponds specifically to the central executive, which was viewed as just one part of a working memory system. Although complex span tests have a structure that makes them difficult to explain fully through slave system functioning, it is unlikely that these systems play no role in task performance. That is, even though the processing element of the tasks is not particularly compatible with the memory-oriented characteristics of the slave systems, and also trials are extensive and therefore difficult to model within

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conventional accounts of the labile and rapid nature of slave systems, it would seem intuitively likely that such systems could support at least some of the retention load of complex span trials. It is interesting in this context that La Pointe and Engle (1990) reported robust word-length effects in adults’ operation span, whereas Lobley, Baddeley, and Gathercole (2005) reported phonological similarity effects in adults’ complex span (although see Copeland & Radvansky, 2001; Tehan, Hendry, & Kocinski, 2001). Yet the link between any central workspace responsible for complex span computations and the slave systems remains underinvestigated.

III. The Development of Working Memory Baddeley’s (1986) working memory model (WMS) was proposed as an account of cognition in its mature form. Nevertheless, it has been applied with considerable success to the memory performance of children and can assimilate a number of phenomena in the development of memory. We briefly note some of the explanatory power of the working memory model for development of immediate memory (see also Hitch, 2006), before we discuss in detail the development of complex span performance. Initial evidence that the working memory model might be applicable to children came from research into the development of memory span for words of different lengths. Variation in memory span for such materials was linearly related to the rate at which items could be articulated, and the same line fitted children of different ages and adults (Nicolson, 1981). Thus, short, single-syllable words take less time to pronounce than long, multisyllabic words, and longer sequences of such short words can be remembered. In the same manner, older children pronounce words more quickly than younger children and their span for words is correspondingly larger. Replications have confirmed this robust finding (Hitch & Halliday, 1983; Hulme et al., 1984) and suggested that the development of memory span could be explained in terms of faster subvocal rehearsal in the phonological loop. An alternative explanation is that the variation is associated with differences in speed of information processing more generally rather than articulation per se (Dempster, 1981). However, direct comparisons of these two views implicate speech rate (Hitch, Halliday, & Littler, 1989, 1993). Subsequent research went further in showing that, unlike older children and adults, 5-year-old children were sensitive to the word length (and phonological similarity) of memory items only when they were presented auditorily. When the same items were presented as pictures of nameable objects, 5-year-olds’ recall was not sensitive to the phonological properties of the object names but it was affected by the visual similarity of the stimuli (Hitch et al., 1988; Hitch, Woodin, & Baker, 1989). This observation suggests that the 5-year-olds relied on visual memory representations (and therefore the VSSP) for visual stimuli while

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relying on the phonological loop for auditory stimuli. In contrast, 11-year-olds’ recall was affected by the phonological characteristics of object names, but was not affected substantially by visual similarity, suggesting that these children translate the pictorial memory stimuli into verbal codes (by naming the objects) and retain the resulting information in the phonological loop. This developmental shift from a (more passive) reliance on the original memory stimulus to a (more active) reliance on a recoded version of the memory stimuli is consistent with the idea of a multicomponent modality-specific working memory system (Baddeley, 1986). Another line of research on the development of working memory focused on changes in the capacity for combining memory and processing operations. In work that, although published subsequently, had helped motivate Daneman and Carpenter’s (1980) reading span paradigm, Case, Kurland, and Goldberg (1982) developed a counting span task that involved a sequence of separate visual displays, each containing several target objects as well as distracters. Children counted the number of target objects on each display and later attempted to recall the count totals. Case et al. (1982) observed a linear relation between counting span and the speed at which children of different ages could count the items in the displays. They also found that when adults were artificially slowed by requiring them to count using nonsense syllables, their counting spans were correspondingly reduced. To explain these data, Case et al. used the concept of WMG as a central workspace (see also Case, 1985). Faster processing was taken as an index of reduced demands on central resources, leaving more space available for storage. Thus, developmental reductions in the resources needed to support processing result in an increase in the resources committed to memory operations. The line of research begun by Case et al. has proved highly influential, with applications, for example, to the analysis of learning difficulties (e.g., Siegel & Ryan, 1989; Hitch & McAuley, 1991) followed by the theoretical developments that we focus upon in this chapter. Studies of the development of working memory through to adulthood have, for the most part, been about the development of memory among primary school children (i.e., 5- to 11-year-olds). Several factors seem to contribute to this focus; we identify four here. First, a number of early and influential studies (e.g., Case et al., 1982) focused on this particular age range. Second, research described previously has pointed to a number of quantitative and qualitative changes in shortterm memory over this age period. Studies of complex working memory have examined whether parallel changes might be found. Third, changes in primary school represent an important developmental phase in which skills such as reading, mathematics, and communication develop substantially. This period presents a major opportunity to assess whether working memory plays a substantial role in the acquisition of knowledge and scholastic attainment. Finally, there is a

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methodological rationale, in that research on preschool children, for example, has often involved different tasks (e.g., studies of working memory in preschool children do not include complex span type procedures; Hasselhorn, Mähler, & Grube, 2005; Schneider, Lockl, & Fernandez, 2005) and the correspondence between various paradigms is not always clear. Thus, while one cannot afford to ignore conclusions that can be drawn from wider age ranges or indeed from life-span perspectives (e.g., Hale et al., 2007; Swanson, 1999), a number of factors have converged on the prevalent focus on children of primary school age.

IV. Explaining Complex Span in Children As explained previously, Case et al. (1982) proposed that developmental changes in counting span are the consequence of changes in the processing efficiency of counting. As children grow older and counting becomes easier, resources are progressively freed for memory functions. Complementing this result, when adults attempt a difficult form of counting, their counting spans are correspondingly reduced. However, one problem with this account was the absence of direct evidence for resource-sharing, leaving open the possibility of alternative theoretical interpretations. One such possibility comes from analyzing multidigit mental arithmetic performance in adults, in which accuracy can be shown to be limited by the length of the intervals over which temporary information has to be held between successive single-digit operations (Hitch, 1978). In a similar spirit, Towse and Hitch (1995) suggested a simplistic alternative account of counting span in which the speed of counting is important because children who count quickly reach the point of recall earlier. The tendency for information in working memory to be lost over short filled delays implies that children who count quickly are in a better position to remember the relevant items. Towse and Hitch (1995) found that when children enumerated displays that differed in both processing difficulty and completion time, span was higher in the easier condition. However, when materials differed in processing difficulty but were comparable in total completion time, counting spans did not differ. This led Towse and Hitch to suggest that children may switch between the two competing requirements in span, of memory and processing operations, rather than sharing resources between them. Accordingly, the time required to complete processing operations and in turn the opportunity to forget may affect span. Towse, Hitch, and Hutton (1998) offered convergent evidence for the view that the temporal dynamics of task events are relevant to working memory span. They noted that if the sequence of processing episodes begins with a short (brief) episode and ends with a long (pronounced) episode, then retention commences sooner than in the reverse case, in which the first episode is long and the last is

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short. Towse et al. (1998) reported significant differences between these two orders of presenting stimuli for children’s counting span, operation span and reading span, such that sequences ending with long processing episodes led to lower spans. These findings support the task-switching idea that the duration of retention is relevant to performance. At the same time, Towse et al. (1998) found no systematic and consistent difference in the efficiency with which children completed the first processing episode (at the start of the sequence, when there was no concurrent memory load) and the final episode (when concurrent load should be maximal). These data do not support the resource-sharing account, casting doubt on the idea that there is a direct, trading relation between processing and memory. Task-switching offers an explanation for developmental changes in working memory span that is alternative to that proposed by Case et al. (1982). There are large and pervasive changes in the speed of information processing throughout childhood (e.g., Kail, 2000; Kail & Park, 1994). If older children complete the relevant processing operations more rapidly than their younger counterparts, then the working memory trial will be shorter for them. This places older children at a considerable advantage in terms of within-trial forgetting. Processing speed can be important in other ways too. Thus, an older child—being on average a faster child—may be able to use the additional time to perform memorization operations more effectively. The link between working memory span and developmental differences in processing speed can also be extended to an account of individual differences. That is, even within an age group, some children will be faster processors than others, and this may give them an important advantage. The task-switching account suggests that an important limiting factor in working memory capacity is the persistence of memory representations (or, phrased from the opposite perspective, the rapidity with which temporary information is lost). When an individual is “switched away from” memory activities, representations become less accessible. Such forgetting may occur more quickly in some experimental circumstances, and the impact of processing may be more pernicious for some individuals. However, the dominant approach to measuring working memory capacity is in terms of the number of items that can be retained in complex span. Towse et al. (2005) caricature this standard methodology as encouraging a “suitcase” metaphor for memory, in which size is the all-important property. The foregoing analysis suggests that an alternative viewpoint might be helpful, whether as a complementary or a competing conceptual dimension, in which the focus shifts from the size of working memory to its longevity. One alternative to the suitcase metaphor is that of an insulating vacuum flask, the function of which is to maintain for as long as possible the initial temperature of the contents (seen as analogous to the quality of the memory representations in working memory). Because the insulation of the flask is less than perfect its

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contents will eventually have the same temperature as the ambient environment. Thus, in terms of memory representations, the point will come at which their original temperature is no longer discernible. Of course, each of these metaphors is inexact and fails to capture the undoubted complexity of working memory phenomena. In addition, the use of different metaphors might be taken to suggest that the approaches are exclusive to one another, and little can be done to bridge them; the metaphors involve very different things. In truth of course the psychological dimensions may be closer together. Although it would not be profitable to take them too far, considering crude metaphors may nonetheless yield a distinctive advantage. As Broadbent (1957) noted with respect to mechanical models of attention and memory, since the metaphor is palpably not a full description of what really happens in the brain, psychologists are less likely to mistake the suggestion for speculative neurology and so will focus on the essence of the theory rather than irrelevant properties of the model details. Spurred on by this perspective that working memory may reflect the temporal period over which memories can be accessed, Towse et al. (2005) attempted to assess the endurance of working memory representations more directly. They presented children with a temporal variant of the complex span procedure in which a fixed number of “processing plus memory” episodes was presented on each trial. Across a set of trials, the duration of the processing operations was progressively increased to find the limit beyond which accurate recall of the memory items was no longer possible. In this way, they measured the endurance limits of working memory, referring to this in generic form as “working memory period” to contrast with working memory span. Because the sequence length in the period task is constant across trials, the number of items that must be remembered is not the principal constraint. Towse et al. (2005) studied 8-year-old children and administered tests of operation period (in which children completed four arithmetic problems and later recalled the solutions) and reading period (in which children read three sentences and later recalled the words used to complete the sentences). The cognitive operations were initially brief (e.g., in the case of operation period, “5 ⫹ 1 ⫽”) but over sets of trials they became more protracted (“5 ⫹ 1 ⫹ 1 ⫺ 1 ⫽”) so that the processing phase of the task became extended. As is common with span paradigms in children, administration continued until recall accuracy dropped below a threshold level. Both operation period and reading period tasks had internal coherence (for example, there was test–retest reliability that matched or exceeded the level for working memory span) and external, predictive utility (e.g., reading period was significantly associated with reading skills as well as number skills). These observations support the notion of a measurable temporal boundary to the retention of information and show that this factor is related to cognitive abilities. Interestingly, working memory period and working memory span were clearly

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correlated. This is consistent with the idea that endurance capacity and span size are different reflections of the same underlying constraint. However, the data leave open whether the two measures have unique as well as shared properties. Extrapolating from the data, one might predict that working memory period will increase with development, which suggests that the persistence of memory, and not just the size, increases with age (see Cowan, Saults, & Elliott, 2002, for a discussion of evidence that rates of memory decay change with age). Subsequent data confirm this prediction about developmental change in working memory period (Towse et al., 2006; see also next section). It is important to recognize that the analysis of working memory period has not demonstrated that the sheer length of the processing events has necessarily caused the observed forgetting (see Killeen, 2001, for comments about different types of causality, and Towse & Cowan, 2005, for application of these ideas to working memory phenomena). A number of causal factors are possible (some of which we consider subsequently), and we merely argue that the working memory period paradigm offers support for the view that (for whatever reason) the temporal dynamics of relevant tasks constitute an important parameter for a better understanding of the concept of working memory.

A. EXTENDING OUR UNDERSTANDING OF THE ENDURANCE OF WORKING MEMORY Towse et al. (2005) described data from the working memory period task in children, but not in adults, and they described data for each instantiation of the period task separately. Data from adults are very useful, however, even in a developmental context, because they can identify an end point for a developmental trajectory. They can illustrate how development can occur through both qualitative changes (for example, in the strategy used; see Halliday & Hitch, 1988) and quantitative changes (for example, in the memory gains yielded by increases in articulation rate; Nicolson, 1981). So it is possible that working memory period is a functional measure only at a certain point in childhood; its effect and impact being just transitory. We therefore report a preliminary and small-scale dataset that investigates links between working memory measures. Ten adults were recruited from a participant pool at Lancaster University. All had previously completed two reading span tests as part of a separate research project carried out some weeks earlier in the same laboratory. In those tests, participants read aloud an incomplete sentence that appeared center-screen, and they supplied an appropriate word to finish the sentence. There were two forms of the task; in one version, it was this sentence-final word that formed the memorandum. In a second version, the computer supplied a separate and unrelated word following sentence completion, and

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this formed the memorandum. Participants recalled the memoranda and their order through the use of a response-choice display on a touch-screen monitor. The target memoranda were shown in random spatial positions, along with two answers from a previous trial and two words that came from the sentences (but were not the memoranda). Participants touched the screen at the location of words to indicate their recall choice. The sequence length of reading span trials varied between two and five. Counting period involved the presentation of five visual arrays in which target objects (red, filled, horizontal rectangles) were accompanied by nontarget objects (red, filled, vertical rectangles; red, unfilled, horizontal rectangles; and red, unfilled, vertical rectangles). Participants counted the number of target objects on screen. After they declared the answer, the computer supplied a separate word, which formed a memorandum. Participants completed the recall of words verbally. The assessment of counting period began with three trials in which there was a high ratio of targets to distractors, so that targets could be rapidly identified and the processing episode would be brief. Providing that participants correctly recalled memoranda from at least one of the three trials, the ratio of targets to distractors decreased so that processing episodes gradually became more protracted, thus placing greater stress on the endurance limits of working memory. Reading span was measured as the number of words recalled from correct sequences. Counting period was measured as the number of correctly recalled sequences. Period correlated with the combined span scores, r(8) ⫽ 0.80, p ⬍ 0.01, and with both the reading span test involving independent words, r(8) ⫽ 0.68, p ⬍ 0.05, and (though nonsignificantly) the reading span test involving sentenceterminal words, r(8) ⫽ 0.60, p ⫽ 0.07. Given the very modest sample size, strong conclusions would not be warranted. Yet the data are relevant in confirming the initial report from children (Towse et al., 2005) that it is feasible to take simple measures of the endurance limits of memory and that such measures have some psychometric stability. Moreover, the data also advance the case for the generality of working memory period as a family of tasks. Just as working memory span is a generic paradigm involving processing and retention, in which each can take a number of different forms (Turner & Engle, 1989; Bayliss et al., 2003), so working memory period can involve counting, arithmetic sums, or reading. The claim here is not that all these procedures are isomorphic with each other. Yet the associations do point to similarities and help to bolster the belief that one is measuring some common cognitive trait or phenomenon. The size of these correlations between span and period are perhaps all the more notable because the recall methods differed across assessment. On span trials, participants selected their answers from a choice presented on a computer screen, with both

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target and lure answer candidates. In contrast, period trials involved the more conventional verbal recall. Moreover, the interval between assessments is quite substantial, and the test–retest reliability of span itself is not always very large (Waters & Caplan, 1996; Towse et al., 2005). As with Towse et al. (2005), the data do not require us to conclude that it is the passage of time that is directly responsible for the loss of integrity of the memory items in counting period. Later levels of the counting period task offer more opportunity for forgetting, because more trial time is occupied by object enumeration. Yet this forgetting could be viewed in terms of, for example, reduced memory item discriminability or the impact of interference. For example, according to inhibitory accounts of working memory (Hasher, Lustig, & Zacks, 2007), a memory target becomes difficult to discriminate from competitor representations because the latter are not inhibited entirely. Moreover, the inhibitory strength of representations may be relevant to the speed with which information is forgotten during episodes occupied with processing activities. Regardless of the precise explanation, the data underline the idea that capacity per se—the number of chunks or things held in memory—is not the only relevant dimension to consider in the conceptualization of working memory. Accordingly, considered together with other supportive data (e.g., Ransdell & Hecht, 2003; Towse et al. 1998), we conclude that task-switching is relevant to a variety of working memory span paradigms as well as to different experimental and individual difference phenomena. However, we do not propose task-switching as a complete account of either working memory performance or its development. There are several reasons to acknowledge the incompleteness of the model and it is worth briefly identifying some of these. Conceptually, Towse and Hitch (1995) noted that counting span cannot be explained entirely on the basis of the duration of the processing episode. As a processing episode is reduced further and further, there must be other constraints and limits that shape retention levels, such as within-list interference (for a thorough review, see Cowan, 2001). Empirically also, it is clear that there is not a 1:1 relation between processing duration and memory performance. For example, using an interpolated task paradigm, Towse, Hitch, and Hutton (2002) reported data in which slight differences in the length of the interpolated task (produced by differences in the time to complete the final elemental processing operation) were not accompanied by differences in the retention function. Although this could be an issue of sensitivity with respect to the integrity or state of memory representations, it also suggests that there is more to memory performance than the length of the delay. Therefore, we turn next to a discussion of several relevant studies that point to possible elaborations of as well as alternatives to the simple task-switching approach.

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B. BEYOND THE SIMPLE TASK-SWITCHING MODEL 1. The Chronometry of Recall The task-switching hypothesis offers an explanation for the interplay between events that occur during the acquisition and attempted retention of memoranda. However, this phase forms only part of the entire trial structure, because the memoranda must be produced at the point of recall. An increasing body of evidence, principally from STM but also WM paradigms, shows that recall processes can be complex and can affect performance. Cowan et al. (1998) offered evidence from STM recall that individuals engage in list-wise memory search processes among recall candidates. These processes are sensitive to lexical properties (and thus are slower for nonwords; Hulme et al., 1999), and recall speed is dissociable from rehearsal, with both contributing to explanations of recallability (Cowan, 1999b). In sum, processes during recall are complex and multifaceted. Cowan et al. (2003) reported recall timing data from a number of working memory span tasks administered to children and adults. Of particular note was the finding that recall duration was almost an order of magnitude longer for reading span than for STM measures. Recall from counting span was longer than for digit span, but not nearly to the same extent as for language-based working memory tasks such as listening span. Also, Cowan et al. established that some of the variance in response duration was shared with that between working memory span and ability. Response duration also contributed independently to the prediction of cognitive ability. In the present context, these results confirm that there are substantial processes involved in recall from some working memory tasks. These processes differ in their time course from those in STM, show at least quantitative changes with age, and are associated with the predictive prowess of working memory. Working memory is therefore not just about the maintenance of items in accessible form. It likely involves the recovery of items from a partial state (see also Unsworth & Engle, 2006, for suggestions from adult work that implicate choice decisions at output). Such research does not contradict the task-switching account. It simply acknowledges and explores a separate (and possibly complementary) facet of working memory operations. 2. Time-based Resource-sharing Model Barrouillet, Barnadin, and Camos (2004) reported data challenging the idea that the total duration of processing is the sole determinant of working memory span. Across a series of related experiments, they have shown that one critical bottleneck in performance is the number of memory retrievals that an individual engages in during the processing episode. Whereas Towse et al. varied processing time by

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using short or long problems (e.g., 5 ⫹ 1 vs 5 ⫹ 1 ⫺ 1 ⫹ 1) in which the individual addition or subtraction operations were self-paced, Barrouillet et al. varied the time available for individual operations using an experimenter paced methodology. They presented adults with sequences of successive arithmetic requests (e.g., “ ⫹2,” “ ⫺1”) to apply to a running total maintained in memory. As the rate of memory retrievals increased –– which captures attentional systems –– the number of correctly recalled items declined. Formally, Barrouillet et al. propose that working memory is a function of cognitive load, which is defined as (duration of attentional capture)/(total trial time). Of course, we have attempted to make it clear that the task-switching model does not, and never has, argued that total processing duration is a sufficient explanation for performance. There is a clear need for additional explanations. The task-switching model was proposed as a contrast to the simple view that resource difficulty was the driver of working memory span performance. Resource demand is an elusive concept that is very difficult to define without resorting to dangerously circular arguments (see Allport, 1980). Nonetheless, the task-switching perspective does not require that the content of processing be regarded as wholly irrelevant. Processing difficulty could be a proxy for a number of dimensions of mental activities that may, indeed, have a bearing on working memory. Thus the argument that the number of memory retrievals is important has a significant advantage to it, partly because it is a much more concrete, objectively measurable variable, one that can be assessed for its potency. Barrouillet et al. (2004) argue that memory performance may be affected by a form of what we term here micro-task-switching. That is, participants may choose to reinstate or reactivate memory representations during the processing activity—within any particular processing episode, switching to and from memory activities—and not just switch between externally defined processing and memory episodes. This seems to be a sensible and potentially important extension of the approach we have advocated so far here. The focus on taskswitching at the macro level—between the experimenter-defined phases of processing and memory—has been driven largely by the surface characteristics of the working memory span task in which processing and memory events take place. Data from children support this view in that, as we have reported, the extent of processing and the rate of processing are variables that contribute to working memory scores (Hitch et al., 2001; Towse & Hitch, 1995). Children’s strategic decision to intersperse memory activity during processing may add a separate, orthogonal aspect to memory performance. Indeed, our own research has similarly shown that children are liable to engage in memory consolidation activities before they embark on the processing requirements, which can give the appearance of less efficient task processing (Towse et al. 2002, Expt. 3).

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The extent to which such micro-task-switching activities take place may be quite variable across experimental situations. (Indeed, the early evidence for a trade-off between demands of processing and memory among adults described by Baddeley & Hitch, 1974, was specific, in that it occurred only when the secondary task incorporated vocalization instructions, and thus the trading relation was not ubiquitous.) We suspect, for example, that the extent to which task instructions invite or prohibit rehearsal may play an important though neglected role. Indeed, the explicit prohibition of rehearsal will possibly plant in the child the very idea that the researcher wishes to guard against. (In our work, we currently do not use the word “rehearsal” to children, for this very reason, but instead we emphasize the important of starting to work on the processing activity as soon as it appears and to concentrate on doing so. Moreover, in some experiments, the computer offers feedback to children about the speed with which processing has been achieved, so as to encourage them to regard this as important.) The specific details of the processing operation are quite likely to affect microtask-switching too, in terms of the degree to which it is continuously engaging. This might be phrased more generally in terms of the compatibility between concurrent tasks. Some combinations of mental operations may be naturally interleaved with each other, while in other cases processes need to be completed and cannot be stopped or paused, such that they take place alongside others only contiguously. The memory operations themselves may also be important; for verbal rehearsal of verbal items is perhaps more easily activated than consolidation of nonverbal material, especially if such material is not easily nameable (Brandimonte, Hitch, & Bishop, 1992). Furthermore, the length of the processing activity may well be relevant. If the processing event is quite brief, then microtask-switching may be less important because the processing episode is finished before much information is lost. 3. Representational Overlap and the Nature of Forgetting A separate challenge to the task-switching perspective, also originating with data from adults, was made by Saito and Miyake (2004). Their work focused on two phenomena that have contributed to the framework that we have outlined above; first, the card-order effect, the advantage to span trials when the final card involves a short processing event, and second, the processing-efficiency effect, the comparability of processing under conditions of no load and maximal load (for that trial). Examining reading span, Saito and Miyake presented a series of experiments in which they first replicated the card-order effect in adults (as did Towse, Hitch, & Hutton, 2000). They then went on to show that manipulations of exposure time for the sentence processing materials (adjusting the speed of a moving window through the sentence) could be used to create, on the one hand, brief or extended sentences in which the content was equivalent or, on the other hand, equivalent sentence durations yet with different contents. They found that

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changes to the temporal length of processing did not affect span, but that changes to the content did make a difference. These findings suggested that the sheer passage of time was not critical, but the throughput or amount of processing was. In addition, their data suggested that there was a small but consistent slowing down of the rate at which sentences were processed across the list. Saito and Miyake (2004) argued that their data are problematic for a straightforward task-switching interpretation of working memory data. Because the processing efficiency effect was small, they also regarded it as being incompatible with a resource-sharing perspective (see also Duff & Logie, 2001). They proposed instead a model of forgetting that was based on representational overlap between processing and retention. As the amount of processing increases, so does the opportunity for overlap with those stimuli that the participant must try to retain, and therefore the degree of forgetting increases. The duration of processing would tend to be associated with forgetting because, as a rule of thumb, it will offer an indication of how much processing takes place. But the degree of overlap between processing and memory is held to be the more important causal variable. It was also argued that this could explain the processing efficiency effect, with overlap producing interference for reading speed as well as retention performance. It is illuminating to consider this research in a developmental context. For example, although it is possible to show that the processing efficiency effect, a slowing down of reading under memory load, can be found under some circumstances in children’s data (Hitch et al., 2001, when allowing for the influence of outlier data) as well as in the adults tested by Saito and Miyake (2004), under some circumstances children’s data show a reverse pattern: that is, processing is more efficient at the end of a trial than at the beginning (e.g., Towse et al., 1998, Expt. 1; Towse et al., 2005; Expt. 2). One might also expect a greater processing efficiency effect in other working memory span tasks like operation span or counting span, where the similarity between processing and memoranda should be greater. The data do not seem to bear this out in a straightforward manner. We have taken this lack of consistency to signal that processing efficiency differences may vary according to a number of strategic processes deployed to tackle the task (and perhaps especially for reading span), rather than to some inherent property of the system faced with the need to juggle both processing and memory demands. Another possibility, though speculative, is of a developmental discontinuity of performance. That is, among children the processing efficiency effect may not be particularly reliable, and when it appears it may do so for reasons other than representational overlap. Through development, the effect, while subtle, may become more stable. Empirical work would be required to substantiate this possibility, of course. We also view aspects of the representational overlap view of forgetting as resonating closely with ideas about the reconstructive nature of reading span recall (Cowan et al., 2003, see above). Cowan et al. suggest that participants may use

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information retained or inferred from sentence processing in order to reconstruct the target memory item. In other words, information from the processing episode may scaffold recall. In this way, processing can provide a supportive context for recall. Nonetheless, this view suggests that processing and retention are not exclusive activities, but actually overlap. The conclusions from Saito and Miyake (2004) are really quite similar to this, although they focus on the aspect of overlap that is harmful for retention (⫽similarity-based interference) rather than helpful (⫽the provision of a recall context). One might then view these as two sides of the same coin. A point of difference is that we regard the ideas of taskswitching and recall reconstruction/overlap as relevant adjuncts to each other, rather than alternatives. They focus on separate aspects of the task and can explain different types of behavioral data. We suspect these theoretical perspectives may be able to coexist rather than be seen as competitive accounts. 4. Analyzing the Building Blocks of Complex Working Memory Span A research program developed by Jarrold and Bayliss (2007; see also Bayliss et al., 2003) offers a valuable additional perspective, because they have developed a complementary research paradigm and, through this, they offer data that at once support and challenge the task-switching model. An important aspect of the approach that they bring to bear is the componential analysis of complex working memory performance and their ability to assemble complex span tasks in different forms and examine both manifest and latent variables that lead to overall scores (in this respect, see also Towse & Houston-Price, 2001b). As will be clear from the discussion so far, complex memory tasks commonly involve a sequence of discrete processing episodes together with a memory item that accompanies each episode. (This memory item may be linked to the processing, indeed may be the product of the mental activity such as the total number of objects in the array, or it may be a semantically unconnected item that is just yoked to the processing in terms of its temporal position.) For example, the participant may read aloud and complete a sentence and then retain the final word for later recall (see Leather & Henry, 1994). The complex memory span task discussed by Jarrold and Bayliss (2007) involved the combination of object selection as a processing activity with retention of information about that object as a memory activity. Nonetheless, object selection could be set to involve a language process, relating to the prototypic semantic properties of a word (presented with the word “grass,” participants found a green object; presented with “banana,” a yellow object). Alternatively, object selection could be the result of visual search for an object property, such as a beveled edge unique to one item, or a conjunction of visual properties that uniquely identified one item. And the information to be retained could either be visuospatial (specifying which of several object locations had been identified as a result to the processing task) or more verbal (remembering a number within the selected object).

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There were other important characteristics of the experimental design. For one thing, each of the processing episodes occupied a constant amount of time. That is, in contrast to typical working memory span tasks, in which processing episodes are completed at a speed largely determined by the individual (for related issues, see Friedman & Miyake, 2004), here the processing episode used a fixed window. Also, the ability of participants to carry out the task components was assessed separately from their ability to carry them out together. Consequently, children were assessed not only on the overall complex span test, but also on color word search, visual search, object location, and object property (number) memory. Analyses of performance on this task support a number of conclusions (see Jarrold & Bayliss, 2007). Processing efficiency was a contributor to complex span performance. This view resonates with the suggestion from the taskswitching account that processing delays can affect the quality of the resultant memory representation. In addition, there were domain-specific contributions to overall performance and residual variance that was argued to represent the executive control demands of coordinating the different operations. The finding that task variance could not be explained fully with reference to domain-general processes supports the view that working memory involves multiple processes (in terms of Baddeley’s model of working memory, WMS, the interaction of different systems, and not just the operation of the central executive). Also, memory ability—as measured by the “STM”-like task—contributed variance to complex memory separately from processing ability. This finding is not inconsistent with the task-switching model per se because that framework does not attempt to deny that memory is involved—but it does serve to emphasize that memory performance differs even when processing is essentially controlled for. In the same way, the evidence that the combination of mental operations contributes to complex span performance leads Jarrold and Bayliss (2007) to focus on a broader set of psychological constraints than the original task-switching model encompasses. This is surely appropriate and is clearly part of the message in this chapter too. In the search for elemental and emergent variables contributing to complex span, Bayliss et al. (2003; see also Bayliss et al., 2005) presented processing events for a fixed window. Children who had not made a processing decision before a critical period were shown the answer to ensure that the processing task was completed. Children who responded before the exposure duration had elapsed were shown the memorandum for the remaining time. As Jarrold and Bayliss (2007) acknowledge, this means that children differed in how much “slack” or free time existed after a decision had been made and before the exposure duration elapsed. While processing time overall can be fixed, there exist different opportunities for activities such as memory consolidation, chunking, or whatever. Yet, designing a memory task that incorporates processing activity can

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be awkward; either one allows processing duration to vary, and then statistically controls for this influence afterward, or one controls processing duration, but at the expense of necessarily having continuous engagement in the processing task. In some situations, processing duration can be fixed or matched (see Barrouillet & Camos, 2001), but this is perhaps limited to certain sorts of experimental approach and certain sorts of processing operation. Compromise is all but inevitable, which makes the role of convergent evidence especially important, since one can gradually eliminate the likelihood that methodological idiosyncrasies can explain the gamut of research findings.

V. Taking Developmental Questions about Working Memory Seriously Although an extensive body of important research is devoted to complex working memory in children, discerning a developmental model of working memory is, surprisingly, not straightforward. That is, we know about a number of phenomena relevant to adult working memory performance, and there are several candidate theories that attempt to explain these findings. We also know about a number of phenomena relevant to working memory among children, again with hypotheses and theories about them. Yet, explaining the mechanisms of change, the concepts that create a bridge to explain how changes occur such that working memory grows through to adulthood and changes beyond, is difficult. This is unfortunate for developmental psychologists, of course, who wish to know about the processes underlying age-related change in working memory. It is also unfortunate for those who study adult models too, though the problem is less widely recognized. The difficulty in such cases is that the adult system has not come preformed, but must emerge through developmental processes. As Rabbitt (2005) persuasively argues, A striking weakness of models in contemporary experimental cognitive psychology is that they only describe functional systems that cannot occur in nature because they do not alter with practice, or during childhood development and age related decline, and are identical in all individuals. (p. 1)

These comments very much apply to developmental psychology. Case et al. (1982) are a notable exception in that they proposed an explicit, indeed exquisite, account of developmental change in complex working memory performance. Case (1985) went on to argue that age-related improvements in information-processing skills would yield benefits for memory performance and that as these efficiency changes took place, so more complex mental activities that required working memory representations could be supported. Thus, even though the total amount of mental resources (Case’s, 1985, term was executive processing space) was invariant across age, changes in functional capacity occurred because of a shift in

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the balance of these resources, which stemmed from older children’s greater efficiency in solving tasks (cf. Pascual-Leone, 2000). The pioneering work of Case and colleagues stimulated a large volume of work into children’s working memory. Despite the accumulation of important data about children’s performance, refinements in our theoretical mechanisms of developmental change have been more modest. In addition, accounts have often focused on local or specific hypotheses, such as the contribution of processing content to the amount of forgetting. Even though these have been entirely justifiable in the context of the particular questions that were asked, such work potentially draws away from the larger picture of specifying a developmental view and understanding how adults’ performance comes to take the form it does. A separate issue facing developmental research is the focus of explanation. Since the work of Daneman and Carpenter (1980) and others, adult working memory research has concentrated on understanding variation in working memory, with respect to individual differences in cognitive abilities (such as the psychometric concept of g). However, such differential issues are less dominant within developmental psychology (although that is not to say that they are unimportant), in which they compete alongside issues of typical developmental growth (and mechanisms responsible for change), as well as atypical development, and the appropriateness of instructional regimes (in other words, a child’s receptiveness to certain types of learning environment). Researchers have been able to identify important changes in working memory that occur in development. However, we are some way from understanding these in detail. On the one hand, we have several indications that children and adults do differ in working memory performance. For example, as we have shown previously, processing contributes considerably to children’s performance on working memory tasks, but contributes less to adults’ performance, such that working memory tasks represent memory tasks to a greater extent (Miyake & Friedman, 2004; see also Towse et al., 2000). On the other hand—and perhaps surprisingly—we do not know when these types of shifts take place nor why they occur. Perhaps processing skill crosses some threshold that makes individual differences redundant? That is, we might regard processing skill as a necessary but not sufficient component of complex span. As a result, we might find variation in children’s processing ability that affects span, because their processing ability is quite limited. Yet by adulthood, even “weak” processing skill may be sufficient, so that this is no longer a relevant source of variation. Alternatively, perhaps memory abilities become differentiated so as to increase their importance? As children get older, both the number of available strategies and their effectiveness may increase. As a result, working memory ability may be a more subtle construct in older children and adults and consequently a more important source of variation. As a third possibility, perhaps the manner of coordination or task combination

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affects both processing and memory? Thus, adults may accomplish the dualtask or combination requirements of complex span in a way that is different to children, which could also produce a change in the way different sources of variance are linked.

VI. Theories of Working Memory in Children: an Integration From the perspective of a consumer, one might well conclude that, with respect to models of complex working memory, it is a buyers’ market. That is, a substantial number of theoretical accounts and hypotheses have been proposed to explain working memory performance. One might imagine that it should be possible to compare the various offerings and decide on which is this year’s “best buy” model. Closer inspection shows the decision is not a simple one, however. Hypotheses differ in terms of their explanatory range and power, and the degree of overlap or compatibility between them varies. We suggest that there is considerable merit in trying to review the ground covered and offer an integration between approaches. Perhaps this is, to some extent, subjective cherry-picking between theories. However, it seems preferable to the alternative, whereby one needs to assume that each approach offers both a necessary and a sufficient account of working memory performance (see Towse & Hitch, 2007), which is unlikely to be realistic. Thus, what are the lessons that might be learned from previous theoretical work reviewed here? (a) From the early and seminal research into complex working memory performance (Case, 1985; Case et al. 1982), key lessons can be learned from the broad developmental perspective that was offered. More specifically, we would concur with the belief that there are some continuous or quantitative changes in working memory. And the changes in working memory across age are substantial and important and can draw upon both psychological models and biological changes. In addition, the attempt to isolate some basic information-processing parameters that could account for working memory is very important. For Case et al. (1982), the key to understanding working memory was processing efficiency, because this could have direct consequences for working memory resources. Another important conclusion is that, in line with other theories (but which had focused on adult data), working memory performance is inherently linked to wider cognitive domains, because it helps to service their needs for transient retention. Notwithstanding these conclusions, we suggest that the specific interpretation of data is not as forced as originally thought. That is, resource sharing is not the only explanation for the pattern of age-related changes or the effects of experimental manipulations. We would also note the argument that working memory tasks are not necessarily interchangeable; there may be important differences

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between complex span tasks (Hitch et al., 2001) as well as underlying commonalities that hold them together. This makes it less likely that a single, global account of working memory (WMG) can be successful. To summarize, in the valuable attempt to see the broad picture, one should not lose sight of the need for examining the more specific empirical phenomena. (b) From the research program into the architecture of WMS (e.g., Baddeley, 1986, 1996, 2000), we infer that there is great explanatory power in proposing a multicomponent working memory system in which modality-specific representations can be retained and transformed. Cognitive development can be attributed in part to changes in the deployment of different working memory systems (e.g., the recruitment of the phonological loop for remembering visually presented information via rehearsal) and, following the work of Jarrold and Bayliss (2007), to the increased efficiency of the individual systems. The subsequent suggestion of an episodic buffer within working memory is intriguing, particularly within the context of complex span development. Insofar as working memory span performance need not be domain-specific, and may incorporate semantic as well as sensory qualities and involve active maintenance processes from encoding to reconstruction, the episodic buffer provides a component of working memory that could offer an important, albeit partial, explanation for the phenomena of complex memory (Baddeley & Hitch, 2000). The model suggests that complex tests are likely to be the product of multiple working memory systems, not just one system in isolation. Structural models such as WMS offer a sense of architecture and information flow, but are less successful in addressing issues of cognitive mechanisms and processing content. This is a point of contrast with a more processing-oriented approach such as the embedded-process model (Cowan, 1999a, 2005). The latter identifies a number of parameters that change across age, offers a more explicit account of the (close) relation between immediate and long-term memories, and more easily accounts for memories that contain representation in multiple modalities (see Towse & Cowan, 2005, for a comparison of approaches). (c) We would argue that the task-switching hypothesis can help explain span performance (Towse & Hitch, 1995; Towse et al., 1998) and it has generated an important legacy in several respects, some of which continue. First, it challenged the then-dominant notion that working memory was a trade-off between processing demands and storage requirements. It suggested the value of paying close attention to any causal chain of events between the phases of a complex span task. Second, it also raised the possibility that aspects of working memory capacity could be explained as being an emergent property of the task structure. Individual differences in children’s working memory capacity could be rooted in individual differences in various information processes parameters (whether domain-general or not).

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Third, moving away from trade-off accounts of capacity makes it easier to envisage how span tasks may share features with other immediate memory tasks and theories. Thus, it becomes more realistic to imagine that domain-specific “slave systems” could contribute to complex span (Bayliss et al., 2003). Finally, the task-switching model encourages greater clarity in what researchers mean by the phrase “active” maintenance and raises questions about the nature of forgetting that had been neglected. The logic of task-switching is that participants need not juggle simultaneously and continuously the twin demands of processing and retention. Instead, forget-and-revive cycles may allow more serial processing approaches to be viable, whether one views task-switching as a macro-task strategy (Towse et al., 1998) or a micro-task strategy (Barrouillet et al., 2004). However, it would be a mistake to infer from a task-switching approach that characteristics of retention are unimportant. Task-switching does not mean that forgetting processes can be reduced to the ineluctable decline in recall quality as a function of the passage of time. Retention is assuredly an important independent concept, one that varies among children even after one has attempted to control for processing time (Bayliss et al., 2003). Moreover, task-switching was never proposed as a complete account of complex span performance, and thus there are inevitable limits in its explanatory scope. It draws attention to the need to specify forgetting mechanisms in the task more clearly but it is not surprising that subsequent work has offered alternative or additional explanations that need to be taken on board. (d) Research into recall timing complements and extends what we have learned from the analysis of recall accuracy (Cowan et al., 2003; Haberlandt et al., 2005). A key insight from this research approach is that working memory is more than information maintenance. Information has to be acquired or encoded, and there may be differences in the way that memory representations are created. Furthermore, the representations must be assembled for report, and recall timing has shown that the representations may be incomplete in some important respects. Moreover, analysis showing that specific phases of recall (e.g., the interword pause) contribute to the association between span and ability (Towse et al., 2006) emphasizes the role of recall in working memory. Although considerable progress has been made in understanding recall processes, we are some distance away from a clear understanding of how different phases of a memory task (encoding maintenance and recall) combine and interact to produce memory phenomena. Also, models of recall timing are not yet at the point at which one can be explicit about all the mechanisms by which internal representations drive recall. In other words, we need to acknowledge the incompleteness of knowledge in this area. Moreover, recall can be effective only when there are functional representations to be constructed, assembled, and subject to reintegration. Thus, the study of recall timing does not diminish the need

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to understand what memory representations a child possesses at the end of the maintenance phase of a working memory task. (e) At different points in the present account, we have referred to research from experimental techniques as well as individual differences analysis. The study of individual differences forms an important domain of enquiry, though as we have noted it sits alongside other developmental issues. We believe that a fairly clear message emerges from the relevant research studying the links between working memory and wider cognitive skills, by which we mean scholastic achievement in core curricular areas as well as classroom behavior more generally. There is substantial regularity and coherence in the patterns of variation between children. Those children who perform well on working memory tasks also are high achievers in scholastic attainment, possess strong reasoning skills, and have the capacity to carry out complex sequential behavioral sequences successfully. In these respects, the data give evidence for the realworld importance of working memory. The study of complex span is more than the study of a purely theoretical construct within cognitive science or development; rather, it offers a window into one of the building blocks of children’s attainment and development in a complex world and helps to understand why some children struggle and others do not, on a variety of mental activities. Yet, it is important to inject some caution into the enthusiasm that should be apparent in the ideas just articulated. An important question, surely, is what are the psychological mechanisms that drive children from one developmental point to another? That is, we need to identify the changes that occur to allow older children to accomplish tasks involving complex working memory better and, maybe, in a different way. However, as observed previously, individual differences may not be entirely the same as developmental differences (see Engle, 1996). It is as least possible to conceive of circumstances in which the things that distinguish one child from another of the same age, with regard to working memory, are not the same things that distinguish the same child at different ages. Unfortunately, we do not have strong data to determine where the links or boundaries are between these two topics. A further point is that our objective is to try to understand working memory and to develop satisfactory accounts of this concept and its developmental trajectory. Individual differences may play an important part in guiding us toward that objective and also in generating phenomena that allow a refinement of conceptual questions that may be asked (thereby generating a virtuous symbiotic feedback loop; see Towse & Hitch, 2007). Yet, if explaining individual differences becomes the central issue, that is, if modeling the link between working memory and mathematical skills becomes the end in itself, we risk the situation in which the tail is wagging the dog. We hasten to add this is not at all to denigrate the value of researching the aforementioned link, simply that ideally it would fit within the larger scheme of thinking about what working memory is and how it changes.

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VII. Conclusion In this chapter we have sampled from a variety of empirical evidence on children’s working memory and have considered a number of theoretical positions. The ability to draw upon these is valuable and provides evidence of the active and healthy state of research. It is also apparent that there are considerable adult data of potential relevance. Consequently, working memory is an area in which researchers on adult cognition (and even neurocognitive aging) can converse with researchers who work with children. We began with hypothetical illustrations of how the concept of working memory may be highly relevant to commonplace activities such as mental arithmetic and compliance with classroom instructions. These are far from the only environments in which working memory is important. We have argued against the common view that children’s restricted ability to perform cognitive activities reflects the constraints of a mental workspace that shares its limited resources between processing and memory operations. We have argued instead that a more important factor is children’s tendency to forget critical temporary information while executing subtasks within the overall activity, such as forgetting some numbers while adding others or forgetting one instruction while carrying out another. What determines the amount of forgetting, as well as the processes underlying age-related change, turns out to be a complex matter with no simple answer. Although the time over which temporary information has to be maintained is important, forgetting is not simply a matter of trace decay. It is much more likely that time acts as a general proxy for a range of different processes of information loss. For example, older children’s ability to hold information in working memory more efficiently than younger children may be because they process information more rapidly and are therefore less exposed to forgetting over time. However, it may also be because they are better able to carry out activities to enhance the maintenance of temporary information during pauses within a task or at recall. Similarly, although we have shown that we can reliably measure individual differences in the duration for which a child can hold temporary information, as in working memory period, it would be unwise to interpret such differences merely in terms of trace decay. A range of other factors affect recall, including the similarity relations among traces and the retrieval processes themselves, as evidenced by studies of recall timing in complex span. In the same spirit, we have seen how individual differences in children’s working memory indicate a complex pattern that is not reducible to differences in a single dimension of trace decay, with, for example, independent contributions from memory capacity and processing speed. Developmental differences also seem to follow a complex, multifaceted pattern. Thus although there are undeniably important quantitative developmental

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changes in working memory, of the sort first plotted by Case et al. (1982), we know also that there are important qualitative changes, such as the developmental progression from visual to phonological representations of nameable objects in working memory. Thus, when children make errors in mental arithmetic (or in carrying out instructions) we would argue that this is not just because of rapidly fading memory traces or an overloaded central capacity, but rather it reflects the operation of a complex, multicomponent system of the type proposed by Baddeley (1986, 2000) that can go wrong in a variety of ways (e.g., Furst & Hitch, 2000). Although our conclusion could be dispiriting for those seeking simple and comprehensive explanations, those engaged in assisting children’s development should find it much more encouraging, as there may be many practical ways of overcoming the core limitations of working memory in any given context and so preventing lost learning opportunities or underperformance in core curricular areas.

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DEVELOPMENTAL SCIENCE AND EDUCATION: THE NICHD STUDY OF EARLY CHILD CARE AND YOUTH DEVELOPMENT FINDINGS FROM ELEMENTARY SCHOOL

Robert C. Pianta CENTER FOR ADVANCED STUDY OF TEACHING AND LEARNING, UNIVERSITY OF VIRGINIA, CHARLOTTESVILLE, VA 22908, USA

I. II.

BACKGROUND AND DESIGN OF THE NICHD SECCYD STUDIES ON SCHOOLING THE NICHD SECCYD CLASSROOM OBSERVATIONS AND OUTCOME ASSESSMENTS A. THE NICHD SECCYD PARTICIPANTS B. THE CLASSROOM OBSERVATION SYSTEM AND RELATED SCHOOLING ASSESSMENTS C. CHILD OUTCOMES AND FAMILY CHARACTERISTICS D. SUMMARY

III.

THE NATURE AND QUALITY OF THE INSTRUCTIONAL AND SOCIAL ENVIRONMENT IN CLASSROOM SETTINGS IN GRADES 1, 3, AND 5: DESCRIPTIONS OF CLASSROOM PROCESSES A. GRADE-LEVEL DESCRIPTIONS B. STABILITY OF CLASSROOM EXPERIENCES C. SUMMARY

IV.

ARE CLASSROOM EXPERIENCES RELATED TO FEATURES OF TEACHERS AND CLASSROOMS? A. CLASS SIZE B. SUMMARY

V.

ARE CHILD OUTCOMES ASSOCIATED WITH TEACHER OR CLASSROOM CHARACTERISTICS THAT ARE THE FOCUS OF EDUCATION POLICY? A. CLASS SIZE, TEACHER EDUCATION, TEACHER EXPERIENCE, AND ENROLLMENT IN PUBLIC OR PRIVATE SCHOOL B. AGE OF ENTRY TO SCHOOL C. SUMMARY

VI. DO EXPERIENCES IN CLASSROOMS MATTER FOR DEVELOPMENT? A. CLASSROOM EXPERIENCES AND ACADEMIC ACHIEVEMENT IN THE ELEMENTARY YEARS B. CLASSROOM EXPERIENCES AND SOCIAL/BEHAVIORAL OUTCOMES IN THE ELEMENTARY YEARS C. DIFFERENTIAL EFFECTS OF CLASSROOM EXPERIENCES D. SUMMARY VII. LIMITATIONS OF THE NICHD SECCYD STUDIES ON SCHOOLING

253 Advances in Child Development and Behavior R.V. Kail : Editor

Copyright © 2007 Elsevier Inc. All rights reserved.

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VIII. CONCLUSIONS AND IMPLICATIONS A. THE “DESIGN SPACE” OF AMERICAN ELEMENTARY SCHOOL CLASSROOMS B. WHAT IS QUALITY OF EDUCATIONAL OPPORTUNITY? C. SCHOOLING MATTERS D. FUTURE DIRECTIONS ACKNOWLEDGMENTS REFERENCES

The National Institute of Child Health and Human Development (NICHD) Study of Early Child Care and Youth Development (NICHD SECCYD) is a major prospective study of 1,364 children from ten sites across the United States, enrolled at birth and studied into early adolescence. Included in the study are detailed assessments of children’s achievement and social outcomes as well as extensive observations of the elementary classroom environments to which they were exposed. The study is in a unique position to describe the nature, quality, and effects of schooling in the elementary years in the United States, one of the intersections between developmental science and education. The present chapter synthesizes the work of the NICHD Early Child Care Research Network (ECCRN) that pertains to the nature, quality, correlates, and effects of observed classroom experiences in the elementary years of the children enrolled in the NICHD SECCYD. Specific topics to be addressed include: (1) (2)

(3)

(4)

the methods used to incorporate schooling-process measures into a largescale natural history study of development; describing, from a developmentally informed conceptual and measurement framework, the nature and quality of the instructional and social environment in classroom settings in elementary school for a large national sample of children; demonstrating the extent to which observed classroom experiences and child outcomes vary as a function of input parameters that are the focus of education policy (e.g. class size, teacher education); and examining variation in trajectories of children’s academic achievement and social functioning during the elementary grades as a function of classroom experience and quality.

I. Background and Design of the NICHD SECCYD Studies on Schooling At the outset, we remind readers that schools are designed to direct the course of development in many areas of functioning. For this reason, what takes place in schools is often viewed with the same value-laden lens that is applied to

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families: witness recent debates on the teaching of evolution and creationism, teaching of abstinence and sex education in health classes, or the widespread acceptance of “character education” as a key component of the curriculum. The scope and passion of debate about these topics can be viewed as reflections of the extent to which schools are, in contemporary American society, a means to influence children’s development. Schools are also often the focus of efforts to address social or economic inequities, and when schools are viewed as having such a compensatory role in relation to family or demographic attributes (e.g., Duncan & Brooks-Gunn, 1997; Gambone, Klem, & Connell, 2002), their role, relative to the family, is elevated in perceived importance. As a landmark in developmental science, the Isle of Wight Study (Rutter et al., 1979) addressed the role of schooling in relation to mental health and behavioral outcomes and drew attention to school leadership, focus, organization, and teacher qualities (Rutter, 1982; Rutter et al., 1979). Yet Rutter and Maughan (2002) concluded their summary of 30 years of progress in research on schooling and development with a series of unresolved questions that informed their original work and continue to warrant attention. These questions are developmental and multilevel in nature (see Pianta, 2006) and press for science linking structural features of schools (e.g., finances, teacher qualifications, catchment) with proximal processes (instruction, relationships) and with students’ achievement, mental health, and motivation. Rutter and Maughan (2002) also note the lack of hard evidence with regard to the ways in which developmental processes differentially respond to variation in experiences offered in schools, an issue of moderation. These are the same questions that also drive education science and push for continued refinement of methods and concepts that can advance the development in context paradigm into and through the school years, with attention to schools as context. Notable among studies in which a focus on schooling is integrated within the study of ecologies, processes, and outcomes is the NICHD SECCYD (NICHD ECCRN, 2001, 2002b, 2003b). Originally designed as a nonexperimental examination of effects of child care on development, this study strategically captured structural and process dimensions of the home and childcare settings to which the children were exposed in an effort to differentiate these settings’ contributions to developmental function and growth. As the 1,364 children enrolled in this prospective study moved on to school, assessments included developmentally sensitive observations of classroom settings in first, third, and fifth grades as well as child, peer, teacher, and principal report of the structural and proximal process qualities of the school environment and detailed assessments of child adjustment across multiple domains within that environment. By combining comprehensive assessments of developmental history and experience prior to school entry, with periodic observations in first, third, and fifth grade classrooms and regular assessments of developmental processes and outcomes in

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the school years, the SECCYD offers a unique opportunity to link education and developmental science. The NICHD SECCYD school observations describe settings, teacher practices and behaviors, and social and instructional quality in approximately 2,500 elementary classrooms and as such are the largest collection of classroom observations in contemporary American elementary schools. The capacity to link classroom process data with outcome trajectories and developmental status prior to school entry is a significant advance for addressing topics of interest to educators, most of which have been addressed by two research traditions. In one, observation of classroom processes is undertaken in small-scale studies or ethnographic work, often with nonstandardized measures and without the capacity to connect observed classroom experience to growth trajectories (e.g., Bogner, Raphael, & Pressley, 2002). In the other, large-scale databases containing outcome assessments (most often standardized achievement tests) and a range of structural characteristics of schools, districts, or teachers are analyzed in sophisticated econometric or other multivariate quantitative models (e.g., Clotfelter, Ladd, & Vigdor, 2003; Grissmer et al., 2000), devoid of any observed indicator of children’s actual experiences in classrooms. The work described in this chapter, which uses the NICHD SECCYD dataset to focus on schooling in the elementary years, is distinct from these research traditions by integrating the study of context and processes with that of structural inputs and outcomes; furthermore, with its rich assessments of schooling, it stands to add to the literature in developmental science a perspective on the role of elementary schooling that has heretofore been somewhat tangential to the field (Pianta, 2006). In this sense, the schooling-focused work of the NICHD SECCYD is indeed an advance in the study of child development.

II. The NICHD SECCYD Classroom Observations and Outcome Assessments The NICHD SECCYD originally was designed to examine children’s development in relation to five parameters of child care experience—age of entry into care, continuity of care, type of care, amount or quantity of care, and quality of care. Because it is a nonexperimental study, a broad ecological framework, considering multiple contexts of development, was adopted. For this reason, the study has been as much a study of home, school, and after-school environments and their effects on a range of child outcomes as it has been a study of childcare settings and effects. From the beginning, the study has been distinguished by three strengths: (1) the inclusion of a wide range of theoretical constructs and measures with respect to both predictors and outcomes, many of which have been measured over time; (2) the use of a variety of data collection methods, such as observations,

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performance tests, and interviews, in addition to survey instruments; and (3) the intensiveness of the data collection schedule for the first three phases covering the period of birth through sixth grade (nine home visits, five child care visits, three school visits, nine laboratory visits, five physical health visits that included puberty assessments, and three physical activity visits). The study provides an opportunity to examine schooling experiences and effects in the context of an extensive and comprehensive collection of information on outcomes and settings. It should be evident that the design of the NICHD SECCYD has several strengths with regard to questions in developmental and education science. In education, a host of these questions (and investigations) revolve around a model of schooling inputs and outcomes that posits a set of structural policy levers and inputs that presumably create conditions in schools and classrooms that lead to growth in students’ learning outcomes (Clotfelter et al., 2003; Grissmer et al., 2000; Hanushek, Kain, & Rivkin, 1998). In simple form, this conceptualization posits that classroom processes should mediate the influence of policy/structural inputs. For example, the effects of curricular reform or raising teacher salaries presumably are evident in student outcomes as a function of improving instruction in the classroom (e.g., putting better lessons in the hands of teachers or putting better teachers in the classroom). The importance of this assumption regarding classroom processes cannot be overemphasized, particularly when most policy-related educational research does not directly estimate classroom-level processes (this despite evidence from multilevel analyses that the vast majority of growth attributable to schooling occurs as a function of classroom-level effects, e.g., Nye, Kostantopolous, & Hedges, 2004). The NICHD SECCYD studies of schooling address to some extent the paths in this framework: associations of structural features of schooling with classroom processes and between classroom processes and child outcomes. At the center of this work are the NICHD SECCYD classroom process observations, which in the context of the larger dataset, offer an important perspective. Described in the rest of this section are the methods used in this work, followed by a synthesis of results as they pertain to the links among structural and process features of schooling and children’s social or academic outcomes.

A. THE NICHD SECCYD PARTICIPANTS The contribution and interpretation of the results of the NICHD SECCYD pertaining to schooling are conditioned on an understanding of the nature of the sample of children and families that have been followed over the years and the nature of the sample of schools and teachers that are the source of schooling experiences.

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1. The Children and Families Between January and November 1991, families were recruited through hospital visits to mothers shortly after the birth of a child at ten locations in the United States (Little Rock, AR; Irvine, CA; Lawrence, KS; Boston, MA; Philadelphia, PA; Pittsburgh, PA; Charlottesville, VA; Morganton, NC; Seattle, WA; Madison, WI). During selected 24-h intervals, all women giving birth were screened for eligibility and willingness to be contacted. Of the 8,986 mothers who gave birth during the sampling period, 5,416 (60%) agreed to be contacted and met the eligibility requirements (mother over 18, spoke English, healthy; baby not multiple birth or released for adoption; lived within an hour of research site; move from the area not planned in the next year; neighborhood not deemed by police too dangerous to visit). Of that group, a conditionally random sample of 3,015 was selected (56%) for a phone call 2 weeks later. The conditioning ensured adequate representation (at least 10%) of single mothers, mothers without a high school degree, and ethnic minority mothers. At the 2-week call, families were excluded if the baby had been hospitalized for more than 7 days, the family expected to move in the next 3 years, or they could not be reached with at least three attempts at contact. A total of 1,525 selected for the call were eligible and agreed to an interview. Of these, 1,364 completed a home interview when the infant was 1 month of age and became study participants. The resulting sample was fairly diverse, including 24% children of color, 11% mothers who had not completed high school, and 14% single mothers. Mothers had an average of 14.4 years of education and average family income was 3.6 times the poverty threshold. Over time, the participants remaining in the followup sample at various stages of data collection differed from the children who were recruited but were lost to follow-up. Mothers of ongoing participants typically had significantly more education, had higher family incomes, and were more likely to have a husband or partner in the household and the children were less likely to be African-American. At the time of the sixth grade data collection, about 79% of the enrolled sample children and their families (N ⫽ 1,073) remained active participants in the study, which is a fairly high retention rate for such a long-term and time-intensive investigation. Of this contemporary sample, 23% of the children were of minority ethnicity, 20% of the mothers did not have a partner or spouse, 8% of the mothers were of low education, and 24% of the families were low income. Importantly, because of the NICHD SECCYD exclusion criteria, the sample was less inclusive of children experiencing a range of potential risk conditions and thus the developmental sequelae and schooling experiences associated with these conditions are not reflected in the study. 2. The Schools and Teachers in the Elementary Years Described in this section is the manner in which classrooms were selected for observation, the procedures for which were identical in first, third, and fifth

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grades. Readers are referred to publications (NICHD ECCRN, 2002c, 2005a, 2006b) and Web resources (http//:www.secc.rti.org) for detailed descriptions of the samples of schools and teachers and the procedures/ measurement strategies used at each grade. In each grade, for the sample participants enrolled at that time, schools were contacted for permission for observation and collection of information from teachers. Most children were enrolled in different classrooms, but in at least sixty classrooms per grade there were more than one participating child enrolled. In analyses of effects of schooling on children, the entire sample of children and their corresponding classroom data were used; in analyses that focused on describing classrooms at these grades, a one-child-per-classroom frame was used, excluding classrooms with fewer than ten children enrolled or full-time special education classes. Because some children were retained in a grade and some were accelerated to the next grade, technically the study adopted a “number of years in school” approach to estimating grade levels, which for nearly all children corresponded to first, third, or fifth and is the convention used here. Table I depicts the number of children observed, the number of unique classrooms observed, and the numbers of schools and districts involved at first, third, and fifth grades. These numbers are inclusive of all types of schools, public and private. Importantly, preliminary checks on the classroom observations indicated no significant differences between public and private school classrooms at any grade; therefore we did not specifically analyze or control for type of school in analyses not specifically targeted to address differences by type of school. These classrooms and schools were distributed across more than thirty states at each grade although most were located in and around the cities in which the ten data collection sites were also located. The teachers in these classrooms were always identified as the primary teacher of the child, even when the child may have been taught certain subjects by other instructors. At first and third grade more than 95% of the teachers were credentialed in elementary education and had a bachelor’s degree or higher level of education. Across all grades these were experienced teachers, with on average over 12 years of teaching. In the sample of fifth grade teachers, the

TABLE I Observed Classrooms in Elementary Schools

Total number of classrooms Unique classrooms Number of schools Number of districts

First grade

Third grade

Fifth grade

966 827 747 295

972 780 673 250

956 795 521 301

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overwhelming majority (88%) met state standards for licensure and certification to teach in that state. Teachers’ ages and monthly salary ranges were quite variable. On average, more than 90% of teachers at each grade were selfreported as Caucasian (92%), roughly 3% African-American, 3% Hispanic, and the remainder reported themselves as some other ethnicity. The characteristics of the teachers and classrooms reported above for the NICHD SECCYD sample closely mirror national averages as reported for teachers in the 1993–1994 and 1999–2000 Schools and Staffing Surveys (National Center for Education Statistics, 1994, 2003). Thus, the samples of observed children, classrooms, and teachers were large and diverse, and although not representative of the nation’s elementary schools, this work provides as close to a nationally representative sampling of children’s actual observed experiences in elementary classrooms as is available (see Hamre et al., 2006).

B. THE CLASSROOM OBSERVATION SYSTEM AND RELATED SCHOOLING ASSESSMENTS Observations took place during the spring of the child’s first, third, and fifth grade years between January and June using the Classroom Observation System for the corresponding grade (described subsequently). Teachers completed a questionnaire during that period providing information on their years of teaching experience, monthly salary, extent of post-high school education, and involvement in in-service training activities during the past year and their perception of principal support. Items for this questionnaire were selected from the School and Staffing Survey Teacher Questionnaire, used as a standard part of the Common Core of Data collected on schools through the National Center on Education Statistics (2003). School-level data were also obtained by principal questionnaires and by linking the school to the National Center on Education Statistics Common Core of Data. Classroom observers used the Classroom Observation System for First, Third, or Fifth Grade (COS-1, -3, -5). The COS-5 and COS-3 are identical (NICHD ECCRN, 2005a, 2006b) and are an upward extension and extensive revision of the COS-1 (NICHD ECCRN, 2002c). The focus of these observations is the classroom as well as a specific child and his or her experiences in the classroom. All observations began with the official start of the school day and lasted between 3 (COS-1) and 6 (COS-3, -5) h. Codes index several broad categories: the target child’s behavior, the teacher’s behavior toward the child enrolled in the study, the setting in which the target child was working, and the qualities of interactions in the classroom. Discrete child and teacher behaviors, specific activities, and setting conditions were coded on a time-sampled basis, while

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global ratings of the classroom and teacher were made using a set of 7-point rating scales. Detailed manuals describe these codes and the coding procedures (see http://secc.rti.org). In first grade the following time-sampled codes were used as indicators of classroom processes: academic activities (the activity in the classroom was academic in nature), teacher-directed group activities, teacher positive, child positive/neutral toward teacher, child negative/disruptive, child positive/neutral toward peers, and child engagement (the child was engaged in the assigned activity). A child’s score for these codes was obtained by summing each observational cycle and averaging across cycles. Global ratings on dimensions of classroom quality, teacher behavior, and child behavior used a set of 7-point rating scales (e.g., teacher sensitivity, positive classroom climate, effective behavior management, productivity, stimulation of concept development, quality of feedback). These global ratings result in two factors (NICHD ECCRN, 2002c) that form the basis of two composite indicators of the classroom environment: instructional support and emotional support (see NICHD ECCRN, 2002c). Global ratings of the child’s behavior during the observation included selfreliance (the extent to which the child demonstrated initiative, focus, autonomy, and leadership). In the third and fifth grades, time-sampled codes included measures of the setting (e.g., whole class, small group, individual), activities (e.g., literacy, math, science, social studies, transition/management), teacher behavior (e.g., attends to child, teaches basic skills, teacher analysis/inference, managerial instruction, affect positive, affect negative, disciplines), and child engagement (e.g., whether the child was engaged in the assigned activity). Global ratings of the quality of interactions in the classroom included overcontrol, chaos, positive emotional climate, negative emotional climate, detachment of the teacher, teacher sensitivity, productive use of instructional time, and richness of instructional methods. These classroom-level ratings ranged from 1 to 7. Factor analysis of these scales also provided support for two composites: emotional quality and instructional quality (NICHD ECCRN, 2005a, 2006b). Identical approaches to training and reliability testing were used at all three grade levels. Observers from all ten sites trained on practice videotapes using a standardized manual that provided extensive descriptions of codes and anchor points, prior to attending a centralized training workshop. After the central training workshop coders conducted pilot observations and trained on two more videotaped cases. Following training, all observers had to pass a videotaped reliability test involving six cycles of time-sampled coding and qualitative ratings. Criteria for passing were at least a 60% match with a master coder on time-sampled codes and an 80% match (within 1 scale point) on the global rating scales. All coders passed at these levels on a reliability test before being certified to conduct observations in the field.

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The reliabilities for the fifth grade observations are consistent with those for the other grades and are provided here as an illustration (see NICHD ECCRN, 2006d). Average exact agreement with the master-coded videotape test for the time-sampled codes, estimated by correlation with master coders’ scores, was r ⫽ 0.85. For the global ratings, reliability was estimated as within 1 scale point on the 7-point rating scales. Average reliability for the child and classroom global ratings on the videotaped test was r ⫽ 0.79. Observers each also conducted a minimum of two paired visits scheduled randomly during the data collection window for the purposes of estimating live reliability. Correlations between observers exceeded r ⫽ 0.84 for all but one of the thirty-eight time-sampled codes, with the lower estimate due to the infrequency of the observed behavior. Average live reliability across all global ratings, estimated using correlation, was r ⫽ 0.71. Because some classrooms were attended by more than one study child there were samples of classrooms to examine stability of the observations across days/different children, a form of test–retest reliability. For the time-sampled codes at fifth grade (N ⫽ 54), the average cross-day correlation was 0.83. For the global qualitative ratings of the classroom environment, the average cross-day correlation was 0.88. Similar results were found for the first grade observations when the average cross-day correlation (N ⫽ 63 classrooms) for the time-sampled codes was 0.79 and 0.71 for the qualitative ratings, as well for the third grade observations when the average cross-day correlation (N ⫽ 52) was 0.87 for the time-sampled codes and 0.91 for the qualitative ratings. The 1-day observations reported for these classrooms were reflective of aspects of the classroom setting that remained stable across days (and different children).

C. CHILD OUTCOMES AND FAMILY CHARACTERISTICS Assessments of the child and family took place at regularly scheduled intervals from birth onward and are detailed in a variety of publications (e.g., NICHD ECCRN, 2002b, 2006a). For the purposes of this chapter’s focus on schooling, the assessments of child outcomes from 54 months of age through the end of fifth grade are most relevant. At 54 months and at first, third, and fifth grade, children were administered subtests from the Woodcock Johnson Psychoeducational Battery–Revised (Woodcock & Johnson, 1989), particularly in the areas of reading and math skills and basic cognition. Information was also available on the child’s level of cognitive ability at fourth grade, using the total score from the Wechsler Abbreviated Scale of Intelligence (1999). At every grade from kindergarten onward, the child’s teacher completed the Social Skills Rating Scale (Gresham & Elliott, 1990) and the Teacher Report Form (Achenbach, 1991) at

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the end of the school year. Again, this is a very cursory view of what was a more comprehensive and extensive set of outcome assessments than is being described, and readers are referred elsewhere for more detailed information on those assessments (www.secc.rti.org). The parameterization of these outcomes varies from analysis to analysis, although by and large the focus was on longitudinal modeling of associations with outcome trajectories or analysis of developmental change. D. SUMMARY The methods are described here in sufficient detail to emphasize their standardization, scientific rigor, and psychometric qualities, all critical for any further use in the descriptive and inferential analyses that are described later in this chapter. Although limited in the sense that they may not reflect all of what happens in a classroom, as a set these classroom observations are comprehensive and overlap well with other work (see Berliner, 1987; Bogner et al., 2002; Brophy & Good, 1986). Although limited to 1 day, they appear to be reliable indicators of what occurs in a given classroom (NICHD ECCRN, 2005a). The procedures themselves may be of interest to readers because they describe the feasibility of one of the largest, if not the largest, stagings of classroom observations in American elementary schools. Furthermore, as developmentally informed assessments of a context with social, economic, and developmental importance, these descriptions provide a basis for continued work.

III. The Nature and Quality of the Instructional and Social Environment in Classroom Settings in Grades 1, 3, and 5: Descriptions of Classroom Processes A series of publications (NICHD ECCRN, 2002c, 2005a, 2006b) present results from the classroom observations, describing elementary education in the United States in ways that at times run counter to conventional wisdom and results from smaller-scale, local studies. Following a conceptual justification for this descriptive work, we present results in summary form and their implications. Despite widespread and perhaps unprecedented attention to the qualities of schooling that produce achievement, rarely have schools or classrooms been the focus of direct assays of support and opportunities for learning, particularly for elementary students for whom self-report and surveys are not accurate. This need for information on what happens in classrooms is exacerbated as the dynamic of accountability shifts to focus on how experiences in K–12 classrooms produce

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achievement (e.g., Appalachian Regional Advisory Committee, 2005; Foundation for Child Development, 2005; Hamre, in press; Perie, Moran, & Lutkus, 2005). Serious questions are being raised about the nature and quality of classroom experiences for students in schools already meeting state standards, including the extent to which curriculum and instruction have become so narrow and test-focused as to miss critical competencies in the areas of reasoning, problem-solving, analysis, and motivation (Bransford, Brown, & Cocking, 1999). There is an emerging consensus on the aspects of classroom environments that produce children’s learning (e.g., Bransford, Brown, & Cocking, 1999; Eccles & Gootman, 2002; Hamre, in press). Instructional, organizational, and motivational/ emotional aspects of the classroom each predict gains in children’s achievement. Different studies report the value of specific dimensions of instruction such as “feedback” (Burnett, 2003; Matsumura et al., 2002; Meyer et al., 1993); stimulation of conceptual thinking, language, and analysis; provision of instructional activities that have relevance and meaning for students; and intense, focused implementation of curricula (Bransford, Brown, & Cocking, 1999; Cameron, Connor, & Morrison, 2005; Hamre & Pianta, 2005). The relational, motivational, and social aspects of the classroom are critical to the extent that they engage the student in learning (Eccles & Gootman, 2002; Pianta, 1999; Weinstein, 2002). Qualities of relationships with teachers, including warmth and closeness, as well as sensitive encouragement and support for independence, have each been identified as fostering a climate conducive to learning and contributing to achievement (Brophy & Good, 1986; Pianta, 1999). Middle school students make abundantly clear how important it is that the classroom promotes a sense of autonomy and competence and that the teacher engages students in a personal relationship (see Eccles & Gootman, 2002; Weinstein, 2002). Classroom organization and management are also supports for learning. Gains in achievement and reduced levels of disruptive behavior are evident in classrooms in which expectations are clear, time is used well and productively, roles are clear, and teachers respond effectively to variation in students’ motivation and focus (Burnett, 2003; Cameron et al., 2005; McCaslin et al., 2006; Hamre, in press). Teachers at all levels of training and experience report behavior management and the challenges of handling students’ social interactions and misbehavior to be their single greatest challenge, concern, and need in relation to professional development and support (American Psychological Association, 2006). In the best classrooms, these three dimensions are woven through instructional activities, discussions, and even transitions in a combination of respectful interactions and personal relationships, high expectations, a productive learningorientation, engaging activities that stimulate thinking as well as social interaction, and regular critical feedback and questioning, (e.g., Berliner, 1984; 1987; Brophy & Good, 1986; Pianta & Allen, 2006; Stipek, 1988).

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A. GRADE-LEVEL DESCRIPTIONS The results of the NICHD SECCYD classroom observations in first, third, and fifth grades make abundantly clear, however, that levels of these assets are quite low in American elementary classrooms and exceptionally variable (see NICHD ECCRN, 2002c, 2005a, 2006b; Pianta et al., 2002). The first grade experiences of the children in the NICHD SECCYD indicate low levels of instructional supports of the type just described; for ratings made on a 7-point scale, the average across these classrooms on dimensions reflecting evaluative feedback and conceptual stimulation was a “2” (NICHD ECCRN, 2002c), a pattern evident in observations conducted in a three-site subsample of the SECCYD (Pianta et al., 2002). Contrary to what most assume to be typical in an early elementary classroom, the most frequently observed forms of activity were structured, teacher-directed, whole-group instructional activities: more than 85% of instructional opportunities were offered to 5- and 6-year-olds in the context of large-group instruction or individualized seatwork. In most first grade classrooms, roughly half of the instructional opportunities were devoted to early literacy, while about one-third of the day was devoted to transition or management activities, more than twice what was devoted to early math instruction. Multistage clustering of composites reflecting the instructional and socioemotional dimensions of these first grade classrooms demonstrate that only 15% show levels of both emotional and instructional supports above a rating of “5” on the 7-point rating system used (Stuhlman & Pianta, 2006). To put these rates in context, a study of the extent to which classroom experiences in first grade close achievement gaps in reading for NICHD SECCYD children from high-risk backgrounds (Hamre & Pianta, 2005) indicates that gap closing in first grade occurs when instructional supports are at or above a level of “3” and emotional supports are above a “5”. The picture is not much different for the children enrolled in the NICHD SECCYD when they reach grades 3 and 5 (NICHD ECCRN, 2005a, 2006b) and is consistent with observations drawn from samples of students in fifth grade enrolled in a study of comprehensive school reform (McCaslin et al., 2006). The vast majority of instruction is either whole-group instruction directed by the teacher at the front of the room or independent seatwork. In third or fifth grade, students rarely, if ever, were offered instructional opportunities in small groups (fewer than five students with the teacher), a finding that defies the assumption that small group instruction is a method of choice. As was the case in first grade, exposure to math and science activities in third and fifth grades tends to be far lower than exposure to activities meant to support literacy, although by fifth grade math activities approach 25% of the total instructional opportunity in a typical day. One particularly interesting result, in light of arguments for instructional opportunities that stimulate advanced cognition (Bransford, Brown, & Cocking,

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1999), is that the ratio of basic-skills activities (the type of activity with a “correct” or “incorrect” response) to activities that stimulate reasoning, problem-solving, or analysis was more than 10:1 at third and 7:1 at fifth grade. Cooperative learning activities, or activities in technology, are relatively rare compared to reading, math, or transitions. Ratings of the instructional and social dimensions of classroom interaction in third and fifth grades again displayed, on average, a pattern of very low levels of instructional support with moderate levels of emotional support. Also evident, as was the case in first grade, was a high degree of variability in the classroom codes—the distributions covered the entire range of codes and standard deviations were relatively large.

B. STABILITY OF CLASSROOM EXPERIENCES Subsequent analyses examined associations between the nature and quality of children’s observed classroom experiences in fifth grade and the experiences to which they were exposed in first and third grades (NICHD ECCRN, 2006d). By and large there was little evidence of stability in terms of children’s exposures to high- or low-quality classroom settings across these 3 years of elementary school. The cross-time correlations for emotional and instructional quality were typically nonsignificant or so low (r ⬍ 0.10) as not to reflect meaningful consistency in the rank-ordering of exposures to classroom quality. There was some suggestion that over the elementary years children are exposed to teacher–child interactions that are somewhat less sensitive over time, and there is a slight rise in the level of cognitive stimulation in instructional interactions, even though the average remains low (below 3 on a 7-point scale). This cross-grade set of analyses was expanded to include examination of family and child predictors of exposures to consistently low and high quality across grades 1, 3, and 5 (NICHD ECCRN, 2006d). The origin of this analysis was an attempt to conduct a natural experiment—to evaluate differences in fifth grade achievement and social outcomes for children entering school with varying levels and forms of risk who were then “sorted” into consistently high- or low-quality elementary experiences (see Clotfelter et al., 2003). The experiment could not be conducted—there were too few children exposed to consistently high or consistently low quality regardless of their risk status at school entry. Importantly, the identification of high- and low-quality experiences in classrooms was not based on some absolute criterion (such as a rating of a “5” on the global scales) but rather based on the top and bottom thirds of the distributions on the emotional and instructional quality composites at each grade. In short, exposure to classroom experience was not only highly variable across children/classrooms at a given grade, it was also highly variable within children across grades. Other investigations that have operationalized “effective teachers” in terms of consistent

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links to growth in child outcomes (Sanders & Rivers, 1996) have shown that having such teachers for several years in a row is the key to maintaining gains attributable to a year in a good classroom. Although few children experienced stably high or low quality across the three elementary grades studied, those few who did experience stably poor quality classrooms (a higher percentage than for stably high quality) were precisely those children who needed high quality—they were disproportionately drawn from the bottom third of the distribution in achievement or social skills assessed prior to starting school. The “inequality at the starting gate” (Lee & Burkam, 2002) appears to apply not only to differences in children’s skills but also to the opportunities to which they are exposed once they enter school. However, this tendency toward “tracks” of high and low quality as a function of family or child characteristics is only slight and tempered by the exceptionally high levels of instability and inconsistency. C. SUMMARY Given the pattern of lack of consistency across and within grades, as well as the overall low levels of instructional quality, it is not surprising that the school effectiveness literature yields so little (Rutter & Maughan, 2002). The typical elementary student is not offered learning experiences throughout the instructional day that include opportunities for higher-order thinking, analysis, or inference (Bogner et al., 2002; Dolezal et al., 2003); nor does he or she get to learn or work in small group or cooperative settings. The approach to instruction appears very oriented toward teaching basic skills through whole-group or individual-seatwork practices, perhaps reflecting the national emphasis on performance of academic skills on standardized tests (National Center for Education Statistics, 2003). This pattern persists into fifth grade, when it is generally accepted that most children have acquired basic reading and math skills. Not to be overlooked is the fact that these classrooms are typically emotionally warm and positive places for the children enrolled. Given the scale and scope of these observations, involving over 2,500 elementary classrooms, it is not unreasonable to advance these findings as descriptions of the “design space” of elementary education in the United States.

IV. Are Classroom Experiences Related to Features of Teachers and Classrooms? As discussed earlier, an assumption of much policy-related research and educational policy making itself is that policy levers can influence in-classroom conditions that affect student learning. To the extent that factors such as teacher

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training, experience, or salary; class size; student demographic characteristics; or even students’ prior performance in the year before are related to the nature and quality of classroom environments, such information could be useful to policy or training initiatives at the state and federal levels that seek to improve the value of educational experiences in America’s classrooms (Appalachian Regional Advisory Committee, 2005; Educational Testing Service, 2004; Lasley, Siedentop, & Yinger, 2006). The NICHD SECCYD classroom observations provide an opportunity to examine this assumption in that they allow for examining the direct association between a range of policy-related levers (e.g., teacher experience) and observations of classroom interactions (such as the nature and quality of teaching behaviors) in one of the largest samples of typically developing children for which observations are available. As the findings are presented on this topic, it will be important to recall that these data are drawn from elementary classrooms and so do not reflect what might be the case in secondary settings. At each grade level, 1, 3, and 5, analyses were conducted to examine both zero-order and adjusted associations between teacher education, teacher experience, class size, school size, teacher wages/salary, and the observational composites of instructional and emotional quality/support (see NICHD ECCRN, 2002c, 2005a, 2006b). In almost every case, the zero-order associations were either very small (if significant) or nonsignificant. If evaluated by adjusting for putative family selection factors, most significant correlations were reduced to near zero. When these structural predictors were evaluated collectively in an effort to determine whether their small bivariate associations with observed classroom quality could collectively account for nontrivial increments in explained variance, they accounted for very small, albeit significant, amounts of explained variance in observed classroom experiences: between 1 and 5% based on R2 values (NICHD ECCRN, 2002c, p. 27; 2005c, p. 54; 2006). It should be noted that a number of approaches were used to analyze the potential association between structural parameters and observed processes. One interest was whether any of an assortment of parameterizations of teacher education or experience predicted observed teacher behavior in the classroom (from both the time-sampled codes and the global ratings). Categories of teacher education (e.g., Master’s vs Bachelor’s degrees) and teacher experience (0 vs more; 0–3 vs other, etc.) were examined, as were linear, cubic, and quadratic components of the association between observations and years of teacher education (or experience) in continuous form. In no case did a priori or empirically driven parameterizations reveal consistent significant associations between teachers’ education or experience and their behavior in the classroom beyond very small, unadjusted, effects that were inconsistently scattered across different observational codes. For example, in third grade, more years of teacher education was associated with a more positive classroom climate (r ⫽ 0.08). In first grade,

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teacher experience was unrelated to observed behaviors, but more years of experience teaching first grade showed a significant, albeit small, association with more time devoted to academic activities. In contrast, at fifth grade, the only link between teacher characteristics and observed behavior was for teachers with more years of experience showing lower levels of instructional quality in their classroom teaching (r ⫽⫺0.10). A. CLASS SIZE A more detailed study of class size effects at first grade (NICHD ECCRN, 2004a) was conducted because of the indication from experimental (Finn & Achilles, 1999; Mosteller, 1995) and nonexperimental (Blatchford, 2003; Class Size Reduction Consortium, 2001; Ehrenberg et al., 2001) studies that class size had a small but significant and possibly meaningful effect on student outcomes. However, this work had not addressed whether classroom processes were changed as a function of class size. Two analytic approaches were adopted in this study using the SECCYD sample—a “natural experiment” using the class sizes for which effects were obtained in the experimental work in Tennessee (Finn & Achilles, 1999) and a spline regression approach that examined shifts in the association between class size and classroom processes at different points on the class size distribution (Blatchford, 2003). In the case of the attempt to replicate the Tennessee study, no differences in classroom observations were detected for classrooms fitting the Tennessee descriptions of “large” and “small.” However, the spline analyses indicated that smaller class sizes (below about 18) were associated with more interactions among students, higher quality instruction that tended to focus on concepts and feedback to students, and somewhat more boisterous classrooms, while larger classes appeared more organized and managed (see NICHD ECCRN, 2004a). As was the case for teacher characteristics, even when associations were detected, they were very modest in magnitude. B. SUMMARY That variations in classroom quality and teacher behavior do not appear to be consistently associated with classroom or teacher attributes typically used to regulate teacher quality or ensure some degree of uniformity in children’s experience or instruction (Clotfelter et al., 2003; Darling-Hammond, 1997; Goldhaber & Brewer, 1999) raises questions about what factors should be the appropriate focus of regulation and whether attention to these parameters are the key to raising child outcomes or indicators of educational quality (National Center for Educational Statistics, 2003). For example, because these findings involve a national sample(s) of certified public school teachers, they call into

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question the validity (and ultimately the utility) of the definitions of a “highquality teacher” that currently dominate teacher licensure, training, and certification in the states under the No Child Left Behind Act (U.S. Department of Education, 2002). In fact, the NICHD SECCYD classroom observation results suggest that a child could be exposed to a teacher who meets NCLB requirements for high quality and yet not be offered a classroom experience, emotionally or instructionally, consistent with what those requirements should represent in terms of teacher–child interactions and opportunities to learn. In this respect these results are consistent with analysis of Texas data showing little to no effect of teacher education or experience on student achievement (Rivkin, Hanushek, & Kain, 2000), analysis of elementary schools in North Carolina in which teacher experience has only a very small association with student outcomes (Clotfelter et al., 2003), and analysis of prekindergarten programs in which observed quality, not teacher or program features, predicts children’s gains (Mashburn et al., 2006). In short, the putative link between policy-related levers and classroom processes appears neither strong nor consistent, at least for the policy parameters and classroom processes and behaviors that were measured in the NICHD SECCYD.

V. Are Child Outcomes Associated with Teacher or Classroom Characteristics That Are the Focus of Education Policy? The discussion of schooling research in the NICHD SECCYD now turns to a different “link” in a developmentally informed model of educational effects and influences: the association between children’s achievement and social/behavioral outcomes and exposure to variation in policy parameters used as levers for promoting these outcomes (NICHD ECCRN, 2006c). This focus follows from a long line of work in child care research in which structural features of child care (e.g., type, ratio) are examined in relation to child outcomes (NICHD ECCRN, 1999, 2002a, 2006a) and which generally shows a small, but significant return to children’s development as a function of what are considered to be “better” values of these parameters (NICHD ECCRN, 2006a). A. CLASS SIZE, TEACHER EDUCATION, TEACHER EXPERIENCE, AND ENROLLMENT IN PUBLIC OR PRIVATE SCHOOL These factors were examined in relation to their contribution to growth in academic achievement and social outcomes from prior to school (age 54 months) over the first 4 years of school (K–3), adjusting for family and child care

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experiences prior to school (NICHD ECCRN, 2006c). It should be noted that this question may be the one for which the NICHD SECCYD dataset is the least strong methodologically because of the lack of multilevel information. To the extent that one would want to estimate the effects of school or classroom inputs on child outcomes, having the capacity to attribute variance at the appropriate levels requires a multilevel analysis of nested data (Nye et al., 2004), sampling multiple children per classroom and multiple classrooms per school, for example. Because the NICHD SECCYD is a nonnested study, these results should be interpreted with caution. Each of the four parameters of educational policy that were assessed in this study (NICHD ECCRN, 2006c) plays a prominent role in debates concerning federal- and state-level decisions related to efforts to improve educational outcomes and quality in the United States (e.g., Berends et al., 2002; Nye et al., 2004; Whitehurst, 2002). As one example of the use of these parameters in policy, the federal No Child Left Behind Act of 2001 (NCLB, H.R. 1, 107th Congress, 2001) specifically uses teachers’ educational level as one factor in defining the quality of educational opportunity. Teacher experience and educational levels are the two primary drivers of salary levels and increases in the American educational system and the largest source of costs to districts and so have relevance for a number of policy-related decisions concerning finance (Hanushek, 1986). Class size occupied a considerable amount of attention at the end of the twentieth century, both in the United States (e.g., Betts & Shkolnik, 1999; Ehrenberg et al., 2001; Finn & Achilles, 1999; Hanushek, 1999; Mosteller, 1995) and subsequently in the United Kingdom (Blatchford et al., 2002a; Blatchford et al., 2002b), and a number of local and statewide initiatives to reduce class size followed, in California, for example. Discussions of school reform also focus on vouchers and public financing of school choice (Johnson & Kafer, 2002; Wolf, Howell, & Peterson, 2000); these arguments rely in part on assumptions that attendance at a private school is reliably associated with better outcomes, because private schools function as part of a supply chain in this more market-driven approach. Policies that support student migration to private schools as one mechanism of school choice are in part predicated on the assumption that private schools are of higher quality than the public school(s) from which these children move (e.g., Kupermintz, 2002). Thus, each of these features of schooling—teacher education, teacher experience, class size, and public/private schooling—figures prominently in contemporary educational policy. The NICHD SECCYD, despite the methodological limitations noted previously, offers several unique features for evaluating whether the educational policy parameters noted previously are associated (individually and in combination) with variation in growth in achievement and social competence. First, standardized assessments of children’s academic functioning and teacher/caregiver ratings of social adjustment were conducted prior to school

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entry through third grade, allowing for examination of individual patterns of change that can be adjusted for background and experiential factors to which the child was exposed prior to school entry. Furthermore, most studies of these policies focus on their effects on academic, but not social, functioning despite the fact that the nature and quality of social interactions and behavioral competence in the classroom are key goals of schooling and mediators of academic performance (e.g., Rutter & Maughan, 2002). The NICHD SECCYD analyses adopt two forms of statistical control to adjust for potential selection biases in relation to exposure to variation in policy. First, a wide range of family process and structure variables are used as covariates, an approach that has been adopted in a variety of other studies of education policy (Clotfelter et al., 2003; Connor et al., 2005), although few of these investigations employed the extensive set of demographic and family process controls available in this study. Second, repeated outcome assessments, in which children effectively serve as their own controls, is a strategy used in a number of examinations of questions related to effects of educational policy (Clotfelter et al., 2003; Connor et al., 2005; Duncan & Raudenbush, 1999). Overall, the results indicate little, if any, association between these parameters and children’s outcomes, with the exception of teacher experience, in which the pattern was somewhat consistent. Being exposed to a more experienced teacher over the course of elementary school was associated with children demonstrating lower teacher-reported levels of externalizing behavior and higher increases in vocabulary that in turn resulted in significantly higher vocabulary scores at third grade, a finding consistent with other reports (e.g., Greenwald, Hedges, & Laine, 1996; Whitehurst, 2002). There was little to no evidence that the associations between these features of schooling and child outcomes would be detected in combination (NICHD ECCRN, 2006c). However, when examining contemporaneous associations between the four policy variables and child outcomes not adjusted for early experience and developmental history, it was class size and private/public school attendance—not teacher characteristics— that were associated with child outcomes at grade 3 (see NICHD ECCRN, 2006c). As such, these unadjusted results are consistent with reports of modest associations between achievement (and to a lesser extent social behavior) and factors such as class size (Ehrenberg et al., 2001; Finn & Achilles, 1999), teacher experience (Clotfelter et al., 2003), or private school attendance (see Krueger & Zhu, 2003). Yet apparently the associations involving class size and type of school detected in the NICHD SECCYD sample could have been the consequence of selection and early experience influences; including these predictors in multivariate models resulted in the elimination of these associations and the subsequent detection of effects attributable to teacher experience. This pattern of selection effects eliminating detected associations is similar to that reported by

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Krueger and Zhu (2003) for private school attendance, Clotfelter et al. (2003) and Hanushek et al. (1998) for teacher attributes, and Ehrenberg et al. (2001) for class size when associations attributed to these factors were reduced by adding selection predictors to multivariate models. B. AGE OF ENTRY INTO SCHOOL Perhaps no other policy parameter dominates discussions of early schooling than does the age at which children are eligible (or required) to start kindergarten (see Stipek, 2002, for a comprehensive summary of the issue and research to date). For parents, one of the most frequent questions noted is whether their child is “too young” to enroll (e.g., West, Hauske, & Collins, 1993). Kindergarten teachers view children in terms of their readiness for kindergarten and often as an explanation for decisions to retain children (National Center for Education Statistics, 1993; RimmKaufman, Pianta, & Cox, 2000). Age of entry is an index society uses as an eligibility or selection mechanism for access to public resources and, consequently, an index that triggers potential benefits of stimulation gained by attendance in school. Because, generally, older children tend to show more advanced developmental skills than younger children, changes in age of entry can have effects on the percentages of children who meet certain academic or skill standards and can “boost” a district’s standing on annual standards assessments (Vecchiotti, 2001). Because of the prominence of age as a policy-related feature of schooling with putative direct linkages to children’s outcomes, variations in children’s academic and social outcomes through third grade were examined as a function of age of entry into school, as well as age of entry cutoffs used in many states (NICHD ECCRN, in press). In this study, the effects of age of entry were examined after controlling for the child’s prior experiences at home and in child care and their performance in academic and social functioning just prior to school entry, an advantage of the NICHD SECCYD design that is not reflected in most research on this issue, yet is critical. The study also used three different ways to operationalize age at entry to kindergarten: treating age as a continuous variable, coding the child as having turned 5 (or not) by July 1 of the year s/he started kindergarten, and coding the child as having turned 5 (or not) by September 1 of the year s/he started kindergarten. Neither cutoff metric produced a pattern of interpretable significant results with child outcomes; there were no significant associations detected involving age of entry; and older children were no more likely to be rated as well adjusted by their classroom teachers than children who were younger at the time they entered school (NICHD SECCYD, 2006). In terms of standardized tests of early achievement (NICHD SECCYD, 2006) age of entry was significantly related both to children’s functioning in the fall of their kindergarten year (the point at which the growth curve intercept was set)

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and to measures of change over time (i.e., slope) for several areas of performance. Children who began school at a younger age scored higher in letter–word recognition but received lower ratings from teachers with respect their academic skills than their older peers. Although significant, effect sizes for these findings were generally small (Cohen, 1988). Differences in kindergarten performance in letter–word recognition did not persist through third grade, but third grade teachers continued to rate older children as more academically proficient. With respect to change in achievement between kindergarten and third grade, children who began school at an older age showed greater increases over time on a number of standardized tests of literacy and math skills. In follow-up tests, these differences in terms of growth were also reflected in differences at third grade such that the older the child at entry to kindergarten, the better his performance academically when in third grade. In short, children who were older at entry into school appeared to have somewhat of an advantage in terms of making use of learning opportunities afforded them, although the effects were modest at best. Although statistically significant, effects of age of entry were modest and limited relative to the predictive power of other factors treated as covariates in the analyses reported (see NICHD SECCYD, 2006), such as mother’s sensitivity. In light of strongly held popular beliefs about the power of age being a harbinger of performance in school, these results suggest it should not be accorded such influence when it comes to policies and decisions intended to align children’s developmental status with learning opportunities afforded in schools and classrooms; rather the child’s developmental status and competencies appear more important. It is important to frame the interpretation of the results of this investigation in light of key aspects of the design of the NICHD SECCYD (Pianta, 2006), including repeated measurements of children’s functioning across the first several years of school and accounting for antecedent family background factors and childcare experiences known to covary with both age and outcomes (Stipek, 2002). Because of these design features, especially controlling for children’s levels of functioning prior to entry to school (cf. Graue & DiPerna, 2000), these analyses provide some of the most well-controlled and comprehensive examinations of age-related effects to date.

C. SUMMARY What can be concluded from the findings of the NICHD SECCYD with regard to the association between parameters of interest to educators and children’s educational and developmental outcomes? By and large, there is some evidence for a very small association between certain levers of policy, particularly attributes of

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teachers, and some indication that policies that regulate characteristics of the child, such as age, also have detectable effects on performance in school. Although scattered across a large number of statistical tests, it is likely, given the methodological concerns noted earlier, that embracing the conclusion of “no effects” would be premature. What is surprising, however, is the very small magnitude of associations linking these structural inputs or child attributes and outcomes through early elementary school. In no case did effect sizes enter the realm of “moderate” in terms of magnitude and for the most part the statistically significant results produced effect sizes in the very small range, at a magnitude of less than 0.1. These results are by and large consistent with much of the literature in that, when detected, effects of policy parameters are fairly small. Such instruments for influencing development appear to be very blunt and not particularly potent, given the contexts in which they are currently applied.

VI. Do Experiences in Classrooms Matter for Development? A major topic of research on education effects involves the connection between the actual classroom experiences to which children are exposed and their performance with regard to educational and developmental outcome indicators. In some ways, this is perhaps the most critical question because it truly bears upon the actual mechanisms by which schooling experiences matter for children (Brophy & Good, 1986; Morrison, Griffith, & Alberts, 1997). Yet the extent to which the NICHD SECCYD provides an answer to this question is at the outset qualified by some of the results summarized to this point—that classroom experiences vary widely from classroom to classroom, school to school, and year to year and that such experiences are not powerfully affected by structural attributes of schooling, which in turn do not seem all that related to children’s performance. Schooling may not produce dramatic effects for the average child, beyond influences of family processes, because there may be too much variation and too little potency in classroom experiences expected to produce effects on children and too much slippage with regard to links that should be in place to ensure consistent exposure to high levels of such processes. With this in mind, the results presented here pertain to precisely this issue—do experiences in classrooms matter for children? The NICHD SECCYD is in a particularly unique position to address this issue of “mattering.” It is unique in terms of the depth and coverage of key developmental outcomes and assessment of processes at home, in childcare, and at school that are expected to be related to these outcomes. In education science, no other study has equivalent information on children’s outcomes and experiences prior to school that can be combined with regular assessments of a broad spectrum of school-age outcomes and experiences. In the field of education science “value-added” modeling (Sanders & Rivers, 1996) attributes growth in

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student achievement to exposure to a specific teacher, school, or other educational experience. Yet very little of this work specifies the nature of classroom experience contributing to increased growth nor has it examined growth in relation to prior experiences or developmental status. In this sense “value-added” models, although “developmental” in the sense of examining change, have yet to fully integrate developmental perspectives and designs. The NICHD SECCYD studies of schooling outcomes complement value-added work in this regard.

A. CLASSROOM EXPERIENCES AND ACADEMIC ACHIEVEMENT IN THE ELEMENTARY YEARS Evidence consistently points to the significance of early achievement in predicting future educational accomplishments (Chen, Lee, & Stevenson, 1996). Although two-thirds of America’s first-time kindergartners appear to enter school proficient in the recognition of letters and even more can recognize numbers and shapes (West, Denton, & Germino-Hausken, 2000), a very large proportion of children in poverty, of color, or of non-English-speaking background lack these basic academic skills when they start school, a pattern that appears fairly stable through the elementary years (Alexander, Entwisle, & Kabbani, 2001). The period from age 3 to 8 years increasingly is viewed as a key period for the development of gateway cognitive, literacy, and language skills that are shaped by child characteristics and experiences in family, childcare, and classroom settings (Morrison & Cooney, 2002; NICHD ECCRN, 2002b, 2005b, 2005c). Given that high-stakes accountability testing begins in third grade and ample evidence that achievement trajectories are quite stable as children begin middle school, it seems imperative to understand the extent to which children’s experiences in elementary school classrooms add value over time to achievement growth through the elementary years. Toward that end, although some studies link teachers’ observed instructional practices and relationships with students to student achievement gains in a given year (Dolezal et al., 2003; Matsumura et al., 2002; Meyer et al., 1993) there have been few, if any, attempts to link the observed classroom experiences to trajectories of achievement growth over the course of the elementary school years, particularly in samples that include large numbers of children and classrooms. Identifying the relative contributions of experiences at home and school to academic performance has been a focus of several articles produced by the NICHD ECCRN, articles that have helped clarify the scope and foci of educational policy and practice related to the transition to school. In several of these studies, the developmental precursors of reading and mathematics achievement in first grade were the focus of investigation (NICHD

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ECCRN, 2004b, 2005c). Using structural equation modeling, one study (NICHD ECCRN, 2004b) tested pathways toward reading and mathematics achievement in first grade as a function of experiences in parenting, childcare, and first grade schooling environments in an effort to understand the relative weight that these settings retain in relation to these outcomes and the extent to which mediated or moderated associations might exist. Consistent with the vast majority of research on early literacy, this study demonstrated that first grade reading skills were most strongly associated with prior experiences in the family setting and that such effects were largely mediated by prior academic and cognitive functioning in the preschool years. These results suggest that family and early rearing factors exert an effect on reading and math achievement in elementary school primarily as a function of how they shape the early phases of performance trajectories, which are, in turn, quite stable in terms of individual differences. After adjustments for prior performance, early home and childcare factors, classrooms that spent more time on literacy, language, and math instruction were associated with higher scores on tests of reading achievement, although such effects were small. Thus, in line with expectations (Christian, Morrison, & Bryant, 1998; Downer & Pianta, 2006; NICHD ECCRN, 2002b) early experiences predicted first grade academic performance primarily (although not completely) as a function of associations with emergent academic and cognitive skills and, to a lesser extent, preschool social competence (see Downer & Pianta, 2006). The role that parenting plays in relation to early achievement was also a focus of study, with particular attention to understanding the ways in which mother–child and father–child interaction patterns shape behavioral competencies that facilitate learning and adjustment in the classroom, which in turn are reflected in standardized test performance (NICHD ECCRN, 2006d). In a sense this was an effort to better connect developmental inputs from the family environment with the rather decontextualized output of test performance. Given the ubiquitous reports from this (NICHD ECCRN Care Research Network, 2002b; 2005b) and other work (see Morrison, Bachman, & Connor, 2005) that maternal behavior and qualities of mother–child interaction figure so prominently in achievement, this study considered whether the quality of the father’s sensitive support for autonomy uniquely predicted children’s reading and math achievement at third grade, controlling for the mother’s sensitive support and prior performance. It was hypothesized that fathering could play an increasingly important role in achievement after a child enters school, particularly because of suggestions that father–child interaction promotes autonomy (Cowan & Cowan, 2002; Parke, 2002). For this reason, there was interest in whether the effect of fathering was mediated by the self-reliance the child showed in the classroom and the quality of the child’s relationship with the teacher in the early school years and whether these paths held for both boys and girls.

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Not surprising were results showing mothers’ sensitive support for autonomy in the early elementary years uniquely predicting boys’ and girls’ reading and math achievement at third grade, even controlling for their reading and math achievement at 54 months. As hypothesized, that effect for mothering was mediated by the level of self-reliance the children showed in the first and third grade classrooms, a finding consistent with views that mothers’ support enhances early school achievement through the mediation of the learning-related skills that children bring to the classroom (Cowan & Cowan, 2002; Pianta, 1999). Unique in this study was the finding that fathers’ support for autonomy in preschool predicted increasing self-reliance in boys from first to third grade, which in turn led to higher reading and math achievement in third grade. Interestingly, these results dovetail with studies in which attention and behavioral self-regulation, tested in laboratory procedures, were the focus of attention as mediators of the association between parenting and early elementary school achievement (NICHD ECCRN, 2003a). The general pattern across these studies of early achievement, parenting, and school experiences suggests that parenting influences academic performance in at least two ways. First, parents transmit knowledge and academic-related skills directly to their children in the preschool years—children exposed to enriched parenting know more vocabulary and are more familiar with reading and math concepts—and such skills lead directly to better performance in school. But also, parenting fosters a set of behavioral capacities—autonomy and self-reliance, behavioral self-regulation, attention, following directions, and cooperation—that appear linked to achievement as a function of classroom adjustment skills that enable the child to take better advantage of opportunities to learn. In relation to parenting, the quality of teachers’ social and instructional interactions in the classroom promotes small but significant gains in achievement within a given grade, but, more importantly, interacts with behavioral and familial attributes. An illustration comes from one study using the NICHD SECCYD to examine achievement gains in first grade for children whose kindergarten teachers reported they lacked the very behavioral and adjustment attributes just described as key mediators of success in the classroom. When such children were placed in classrooms observed as high on emotional and instructional support, the gaps in reading achievement that would otherwise be present were eliminated (Hamre & Pianta, 2005). These results, like others reported in the literature, suggest that schooling experiences, although promotive of achievement overall, play an even more important role in moderating risks for poor school performance (see Ladd, Buhs, & Troop, 2002; Morrison et al., 2005; Pianta, 2006). In light of this and other research highlighting the importance of such everyday classroom activities, the longitudinal extension of the NICHD SECCYD through the later elementary years continued this line of inquiry into the study of schooling and the conditions under which children’s development is enhanced

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or undermined. A subsequent investigation (NICHD ECCRN, 2006b), which took advantage of the observational data gathered at first, third, and fifth grades and of repeated assessments of children’s academic achievement at these ages, was designed as an extension of the empirical work at first grade by examining the contribution of teachers’ instructional and emotional interactions to students’ growth in reading and math achievement. Moreover, given the relatively robust indications that boys and children in poverty are more likely to achieve at lower levels than girls or students from middle to high income families (Lee & Burkham, 2002), the study examined the extent to which high-quality instructional or socioemotional classroom experiences across the elementary years moderate these risks. To model math and reading development over time, this investigation relied on growth mixture modeling (Muthén & Shedden, 1999) as an approach to examine change over time because there was evidence of two distinct groups of readers. For the group of “fast readers,” whose trajectories rose quickly and then leveled off at first grade, there were no significant effects of elementary classroom quality (emotional or instructional) or quantity of exposure to reading activities on growth. A different pattern emerged for the “normal readers,” whose reading growth was less rapid and who tended to score somewhat lower by fifth grade than did the fast readers. For these readers, there were positive effects on reading development from the positive emotional climate of the classrooms to which they were exposed. For math achievement, only one latent class was obtained and there were again significant effects for classroom experiences on the growth trajectory of this group. Higher rates of growth in math achievement were related to the levels of emotional quality observed in elementary classrooms to which children were exposed and to the amount of math instruction at third and fifth grades. Thus positive rates of growth in math achievement in the latter half of elementary school (when math becomes more of a focus of the curriculum and instruction—see NICHD ECCRN, 2006d) were a function of exposure to more instruction in math and classroom teaching that promoted a positive social setting. In this study, spanning the entire period from preschool through fifth grade, the limited evidence highlighting the potential influence of proximal classroom processes calls attention to both the amount of exposure to math instruction and the emotional support the child experienced in the classroom. Consistent with expectations that “time on task” matters, and thus that greater exposure to math instruction would facilitate math achievement, results showed that in both third and fifth (but not first) grades, more time spent being taught math predicted better math achievement over and above what would have been expected on the basis of general developmental change. The fact that greater emotional support in fifth grade, which predicted enhanced math achievement in fifth grade, reflected the

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child’s experience in the classroom in general and not exclusively during mathematics’ instruction suggests that the child’s overall positive feelings about school may contribute to improved math performance when the classroom is emotionally supportive of the child (Crosnoe, Johnson, & Elder, 2004; Zins et al., 2004).

B. CLASSROOM EXPERIENCES AND SOCIAL/BEHAVIORAL OUTCOMES IN THE ELEMENTARY YEARS Although the major agenda of school is teaching academic skills, schools are social environments with expectations for behavior and social structures to which children need to adapt. The expected behaviors go well beyond literacy and numerical skills to self-regulation (e.g., involvement in classroom activities, restraining disruptive behavior, attending to the agenda of the classroom, working autonomously), social interactions with adults (e.g., compliance, clear communications, positive social interactions, absence of defiance, or conflict), and positive interactions with peers (e.g., cooperative activity, nonaggressive conflict resolution). These competencies in the early grades, as well as problems in these domains, are important indicators of early school success and harbingers of subsequent outcomes (Entwisle & Alexander, 1999; Ladd & Burgess, 1999; Rimm-Kaufman et al., 2000). On the one hand, teachers often define school readiness in relation to conduct and ability to follow directions (Heaviside & Farris, 1993; Rimm-Kaufman et al., 2000). On the other hand, social and behavioral problems, including inattention, poor impulse control, difficulties following directions and conforming to classroom rules and routines, disruptive behavior, and aggression toward peers, predict continuing problems in adjustment in middle childhood (e.g., Campbell, 1994; Ladd & Burgess, 1999; Schwartz et al., 1999). The social and behavioral competencies children demonstrate in the early grades are therefore of interest as outcomes of prior developmental experiences, as precursors of later functioning, and as targets/goals for schooling influences. Classroom contexts that provide opportunities for learning and socioemotional supports may facilitate the development of self-regulation and social skills with adults and peers; and chaotic and punitive classrooms with little instructional support may contribute to disruption and withdrawal. Teachers’ sensitive behaviors moderate children’s off-task behavior in kindergarten (Rimm-Kaufman et al., 2002) and the overall emotional quality of the classroom setting shapes children’s engagement in that setting, particularly when children are prone to off-task behavior or if the instruction is conducted in large, whole-group settings (Rimm-Kaufman et al., in press). The contemporaneous classroom environment is clearly related to the types of social and behavioral competencies that children display in that setting, as has

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been summarized in an assortment of descriptive papers from this study (NICHD ECCRN, 2002c, 2005a, 2006b; Pianta et al., 2002). In general, across these studies, classrooms in which the overall climate is positive, the teachers are involved and sensitive, and instructional time is used productively have children who are more attentive, engaged, and self-reliant; who have positive or neutral interactions with teachers; and who are not often disruptive. Although these findings may seem obvious, they are not trivial. What teachers do in the classroom matters for children’s behavior in that setting and may have consequences in the present or future. Therefore these links between concurrent classroom experience and adjustment in the classroom must be examined further to detect the extent to which they have significance developmentally. Similar to the examination of family, childcare, and schooling experiences on academic achievement, which was described earlier, a parallel effort examining these multiple factors in relation to social adjustment was conducted (NICHD ECCRN, 2003b). Analyses included extensive controls for children’s preschool levels of behavior, family characteristics, and childcare experiences. After these adjustments, children in first grade classrooms with high instructional support and high levels of structured activity were observed to display more positive behavior toward their teachers than were children in classrooms with less instructional support. High levels of emotional support were also associated with observed self-reliance and engagement in learning. Although these classroom process indicators predicted behavior in the classroom, they generally did not predict contemporaneous teacher or parent reports of children’s positive social skills or behavior problems (NICHD ECCRN, 2003b). However, one exception occurred: mothers reported more internalizing symptoms when their children were in classrooms with low emotional support and high levels of structured activity. Overall these findings suggest that classroom contexts in first grade affect children’s actual classroom behavior in ways that may possibly forecast their adjustment in subsequent classrooms, setting the stage for a follow-up examination. In that study (NICHD ECCRN, 2006e) longitudinal patterns of observed and informant-reported social functioning were examined as a consequence of prior and contemporaneous classroom experience using growth modeling as a means of examining trajectories of social behavior across grades, with classroom experience modeled as a time-varying covariate. With first grade behavior controlled, observed third grade classroom behaviors were associated with the contemporaneous classroom features and there was no evidence that first grade classroom effects persisted. As expected, positive classroom climates at third grade were predictive of more involvement and less disruptive behavior among children, an effect detected for teachers’ reports of more positive adjustment in fourth grade, while children in third grade classrooms with higher rates of discipline were more likely to be disruptive. When the contemporary classroom setting offered more opportunities for collaborative

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work, children displayed more positive interactions with their peers (see NICHD ECCRN, 2006e). In short, the evidence was quite consistent that features of the classroom in which a child is enrolled have their most powerful influence on social behavior in that setting rather than on future behavior. One reason for the lack of prediction may be that children experience different classroom contexts from year to year and, in this sample (see NICHD ECCRN, 2006d) experienced little consistency in either positive or negative contexts from first to third grade. When they change classrooms, children’s behavior adapts to the new classroom environment and possibly undermines a more cumulative effect.

C. DIFFERENTIAL EFFECTS OF CLASSROOM EXPERIENCES Questions of moderation are embedded in all educational research—for whom do particular types of classroom interactions matter most and are different types of interactions needed to produce optimal development for different types of children? In the instructional arena there is strong evidence of moderation. For example, Morrison and Connor (2002) demonstrated that children at risk of reading difficulties at the beginning of first grade (identified on the basis of test scores) benefited from high levels of teacher-directed explicit language instruction—the more teacher-directed, explicit instruction they received, the higher were their word decoding skills at the end of first grade. In contrast, teacherdirected explicit instruction made no difference in decoding skills for children with already high skills on this dimension upon school entry. Highly skilled children made the strongest gains in classrooms with more child-led literacy-related activities. These findings have been replicated in preschool (Connor et al., 2005) and third grade (Connor, Morrison, & Petrella, 2004) classrooms. Moderating effects are evident in social processes as well (Hamre & Pianta, 2005; Ladd & Burgess, 2001; Rimm-Kaufman et al., 2002). For example, RimmKaufman et al. (2002) examined whether teachers’ sensitivity predicted kindergarten children’s behavior for groups of socially bold and wary children, with the bold children demonstrating high levels of off-task behavior and negative interactions with peers and teachers. Although teachers’ sensitivity was unrelated to classroom behavior among the socially wary children, socially bold children who had more sensitive teachers were more self-reliant and displayed fewer negative and off-task behaviors than did bold children with less sensitive teachers. A subsequent study drew upon the NICHD SECCYD to test precisely the possibility that interactions in classrooms can close gaps (Hamre & Pianta, 2005). It examined whether children at risk of early school failure exposed to high levels of instructional and emotional support in first grade displayed higher achievement and lower levels of conflict with teachers than did similarly at-risk

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peers in classrooms that did not provide this support. Two groups of at-risk children were identified: those whose mothers had less than a 4-year college degree and those who displayed significant behavioral, social, and/or academic problems according to their kindergarten teacher. Not surprisingly, these at-risk children, on average, were behind their peers in early achievement even at age 4, and fell further behind their low-risk peers by first grade, and had higher levels of conflict with first grade teachers. Yet not all of these children displayed academic or relational problems in first grade; some were doing quite well, and their success seemed connected to the kind of experiences they had in their first-grade classrooms. If placed in classrooms offering low instructional quality, children whose mothers had lower levels of education, not surprisingly, had poorer achievement than did their peers with more educated mothers. However, in classrooms offering higher levels of instructional quality and support, children with less well educated mothers achieved at the same level as those with mothers with a college degree. Similarly, when children whose kindergarten teachers judged them to be showing considerable adjustment problems in their classrooms were placed in emotionally supportive first grade classrooms, they showed achievement and adjustment levels identical to those of children who had no history of problems in kindergarten. For kindergarten children at risk of problems in first grade, success or continued difficulty in school depended on the quality of their first grade classroom. The instructional and emotional aspects of interactions between teachers and children in first grades closed the achievement gap for children likely to not do well.

D. SUMMARY Quite clearly, classroom experience does “matter” with regard to contributions to development of academic and social skills. In the NICHD SECCYD studies, effects were detected for the emotional and instructional qualities of the classroom setting as well as the amount of exposure, particularly for math, in relation to achievement gains and social skills, even in the context of a design that is not optimal for attributing outcome gains to classroom experience (described later). Importantly, the significant effects are quite small, particularly relative to effects of experiences within the family, a finding that parallels the NICHD ECCRN published work related to child care effects (see NICHD ECCRN, 2006a). What is also clear is that, to a very large extent, performance on standardized tests of achievement and academic skill (which is the coin of the realm in most state and federal policies) is highly stable throughout the elementary years and trajectories in achievement domains are set in motion prior to entering school. In contrast,

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experience in classrooms also has contemporaneous effects on children’s behavior in those settings, a nontrivial result when evaluated in light of the possibility for cumulative accretion of skill as a function of placement in well-aligned classrooms. Finally, to the extent that classroom experiences matter for development, such experiences may indeed matter more for children who are risk exposed or who exhibit vulnerabilities. The capacity to understand and model prior history and contemporaneous experiences in nonschool environments when examining schooling effects is a strength of the NICHD SECCYD.

VII. Limitations of the NICHD SECCYD Studies on Schooling The findings of the NICHD SECCYD as they pertain to the nature and quality of schooling, correlates of classroom experience, and ways that experiences in classrooms and schools intersect with development are limited by several constraints in the study’s design. First, the observations conducted at first, third, and fifth grades, although fairly comprehensive, did not include the entire scope of codes that might be deemed important or relevant. Also, some of the codes themselves were somewhat limited and restrictive, such as is the case for “child engagement” that reflects only limited exposure to an activity rather than a rich and active engagement with a challenging task (e.g., Dolezal et al., 2003). Questions have also been raised regarding the reliability of a 1-day sample for assessing what is assumed to be a stable feature of schooling. It is the case that although the observations were limited to 1 day and did not systematically sample variation across multiple days, subanalyses indicated the estimates to be reliable indicators of what occurs in a given classroom (NICHD ECCRN, 2005a). The children who were observed may not have been “typical” in some way, or attributes of the observed children themselves may somehow have been related to the observations of these classrooms. However, to the extent that the NICHD SECCYD sample reflects a diverse range of family backgrounds as present in the United States, these observations reflect a typical day in school for a large number of children. It is important to note the NICHD SECCYD sample excluded children experiencing a range of potential risk conditions and therefore these descriptive results may not reflect the even wider range of educational experiences of children raised in high-risk circumstances. Also, the observations sample many classrooms in many school systems, with many different children as the targets, a set of conditions that to some extent may randomize some types of error or bias that could be present if the sample of classrooms was small, limited to a single school or district, or focused on children exhibiting a particular characteristic.

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Also of note, particularly in relation to analyses pertaining to school- and district-level predictors of classroom experience or child outcomes, is that this was not a study with a nested design, in which multilevel modeling could be used to allocate explained variance appropriately to child, classroom/teacher, school, or district sources. The conclusions drawn regarding the fairly limited effects of certain educational policy parameters on child outcomes, particularly class size, may be qualified by this limitation. A particularly important limitation of the study design, especially in relation to identifying effects of classroom experience on developmental trajectories, is that classrooms were observed, and achievement outcomes assessed, only every other year. Thus the “pretest” controls for prior achievement, for example, were 2 years past, such as in the case of predicting growth in achievement as a function of third grade classroom experience by having to use first grade achievement as a starting point. In some cases growth modeling allowed for the creation of trajectories of achievement, but nonetheless, obtaining a close-in-time, specific linkage between classroom experience and achievement growth during that year/grade was not possible, as it is in the case of true value-added studies (e.g., Sanders & Rivers, 1996).

VIII. Conclusions and Implications The NICHD SECCYD studies of schooling and development yield a number of general conclusions, some of which are quite consistent with the available literatures, whereas in other cases the results are more controversial or novel and in fact contradict conventional wisdom. On the one hand, the findings that classroom experiences produce small increments in learning for most children and are particularly important for some groups of children are not surprising. On the other hand, results from observations in roughly 2,500 elementary classrooms sampled from a very large number of schools and districts from all across the country provide an unprecedented window on the nature of these classroom experiences and their connection to the levers that are at least assumed to shape them. It is this aspect of the NICHD SECCYD that, although descriptive and fairly simple methodologically, may ultimately shed the most insight into the connection between schooling and development. A. THE “DESIGN SPACE” OF AMERICAN ELEMENTARY SCHOOL CLASSROOMS Observations of a typical day for a typical child in 2,500 elementary classrooms are the best estimate available of the design space of American elementary education (see Hamre et al., 2006). What is that space? Elementary classrooms in

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the United States are fairly positive social settings but from the standpoint of instruction and the stimulation of academic skills and cognition they are places that encourage passivity on the part of learners and participation in acquiring fairly rote and simple basic skills, for which children are not likely to receive feedback on their performance through interacting with teachers nor will they be stimulated to reason or problem solve. Contrary to popular beliefs about the contexts in which children are taught, there is little opportunity to learn in small groups and even less cooperative learning—most instruction is delivered in a large group and skills are practiced individually at a desk. These features of elementary classrooms are quite consistent grade to grade, and most children travel through the grades in classrooms that fit these profiles. It is not surprising then, that in relation to family processes or prior development history, schooling adds only small increments to children’s achievement levels; by and large it appears to be a fairly weak “intervention.” However, it is also the case that classroom experiences can matter quite a bit, particularly for a child who is less advantaged, when that child is placed in a classroom that is the exception to the rule just described, an event with a roughly 15% likelihood. Among the classrooms in the NICHD SECCYD, only 20% in any given year provide students with levels of emotional and instructional support consistent with the kind of classrooms that produce higher than expected gains. No less troubling is the evidence that students fortunate enough to have such support in one grade are not likely to receive it the next years, despite the fact that schooling has the potential to have very powerful cumulative effects when high-quality classroom experiences are aligned over time (Sanders & Rivers, 1996). Unfortunately, exposure to gap-closing classroom quality, although highly desirable from nearly every perspective imaginable, is not a regular feature of early schooling and even less likely for children in poverty or children who enter school with relatively low levels of academic skills. In other words, the odds are stacked against children getting the kind of elementary experiences that close gaps and add value beyond family background (Morrison et al., 2005). At each grade observed, there is also wide variability in the opportunities provided to students—some children spend most of their time engaged in productive instructional activities with responsive teachers who consistently provide feedback, challenges to think, and social supports. Others, even in the same school and grade, spend most of their time passively sitting, watching the teacher deal with behavior problems, exposed only to boring and rote instructional activities. In some cases, even in classrooms right next to one another that share the same materials and curriculum, the exposure of children to high-quality learning and social supports is so dramatically different that one might conclude the difference was planned. In first grade, children in some classrooms are exposed to few, if any, literacy-focused activities, while in other classrooms in the same school, they receive more than an hour of exposure to literacy-related activities, including

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narrative storytelling, practice with letters, rhyming games, and listening. Opportunities to learn are uneven and limited—that is the design space of elementary education.

B. WHAT IS QUALITY OF EDUCATIONAL OPPORTUNITY? Education policies at the federal, state, and local levels use a variety of levers to produce effective, high-quality educational experiences for children (Appalachian Regional Advisory Committee, 2005; U.S. Department of Education, 2002). For example, one of the mandates of the No Child Left Behind Act (U.S. Department of Education, 2002) is that classrooms are staffed by a “highly qualified teacher” and teacher quality appears in numerous state and national policies and reports, is a focus of funding and research initiatives in teacher education, and is no stranger to the editorial pages. As defined by NCLB, a highly qualified teacher must have: (a) a Bachelor’s degree; (b) full state certification, as defined by the state; and (c) demonstrated competency, as defined by the state, in each academic subject he or she teaches (www.ed.gov/teachers/ nclbguide/tookit). For teaching in the elementary grades, most states simply require new teachers to pass a general knowledge test and experienced teachers to meet certain criteria that include passing the same test, accruing experience in the classroom, attending professional development workshops, or serving on curriculum development teams, among others. By these definitions, the overwhelming majority of teachers participating in the NICHD SECCYD classroom observations would meet the NCLB standards as highly qualified in their respective states. If indeed the observations of elementary classrooms described earlier result in an impression of classrooms as providing limited and uneven opportunities to learn, while the teachers who staff these classrooms by and large meet the standards used to regulate their entry into and continued involvement in the profession (and that also allow states and districts to remain in compliance with federal law), then two concerns come to mind. First, the learning opportunities offered in classrooms apparently are not, at present, responsive to the current standard levers of policy and incentive systems. If there is such unevenness and limited opportunity and all teachers meet the definitions for “highly qualified,” then such regulations and definitions are not closely linked to the mechanisms that actually produce opportunities in classrooms to be of much use. Second, and relatedly, these results raise questions concerning the very definitions of educational opportunity used in the United States. For example, if there is concern about equal opportunity to a high-quality educational experience and the current definitions of a “highly qualified teacher” are used as the benchmarks for opportunity, then it is likely that estimates of equity or quality will be at best fairly blunt and inaccurate or, at worst, misleading in terms of being too high (Appalachian

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Regional Advisory Committee, 2002; Educational Testing Service, 2004; U.S. Department of Education, 2002).

C. SCHOOLING MATTERS One of the most persistent questions in educational and developmental studies of achievement is the degree to which both general and specific forms of experience in school add value beyond effects and influences attributable to experiences prior to and outside of school: at home, in the peer group, and in the community (Morrison & Connor, 2002; Rutter & Maughan, 2002). For example, to the extent that educational policy deals primarily with structural features of the school setting, such as teacher education or certification and class/school size, it is critical to examine the extent to which variation in enactment of such (expensive) policies contributes to variation in outcomes beyond accumulated family resources and processes. Other aspects of educational policy call attention to specific classroom practices, for example, in the areas of teaching reading (e.g., Foorman & Torgesen, 2001; Lyon, 2002) or mathematics (Shapka & Keating, 2003). Testing the accumulated contribution to elementary grade outcomes of structural features of schools relative to that of classroom processes and practices potentially has considerable implications for what should be the focus of educational policy. At the same time, these studies have great potential to inform our understanding of basic developmental processes, particularly those related to moderation of risk, in part because the vast majority of educational resources and attention are devoted to strategies intended to moderate the effects of conditions related to socioeconomic disadvantage (Duncan & Brooks-Gunn, 1997; Furstenberg et al., 1999). Despite the limited and somewhat unsystematic nature of classrooms’ support for learning, there is evidence that the aspects of classroom quality observed in this study—emotional support and instructional support—as well as the amount of instruction to which a child has been exposed (particularly for math) contribute to growth in achievement in general for all students and are particularly salient for reducing gaps between groups. Overall there was less evidence that structural features—class size, public/private schooling, teachers’ education or experience— were consistently related to student outcomes. The observations described herein, for which variation appears to be so pronounced, assess features of classroom experience that predict children’s achievement and social functioning, family influences and prior performance, reflecting perhaps what happens in classrooms that accounts for the “value added” of schooling for standardized test performance. More fine-grained analysis of outcomes (or mediators) likely to be more sensitive to classroom experience (e.g., motivations, perceptions of schooling, social relationships in classrooms, attention, and self-regulation) may reveal larger effects for schooling and more about the potential mechanisms through which schools influence the more

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standardized outcomes valued by the public. The NICHD SECCYD dataset contains assessments of such psychological and social process constructs and further work with these is bound to expand the study’s contribution to the connection between the developmental and the education sciences. D. FUTURE DIRECTIONS The NICHD SECCYD continues to collect information about the participants’ experiences and development as they move into adolescence, with most passing through their second year of high school in 2007. The study data collection protocols, since middle childhood, have expanded to accommodate key developmental processes and influences during this period, including assessments of physical activity, cognition, pubertal timing and development, basal cortisol, experiences in the community and with peers/friends, and attitudes that reflect the transition toward the world of work and college. Threaded through this expanded view of development remains a focus on school performance, attainment, and attitudes/experiences related to schooling. Extending the SECCYD into high school offers an unparalleled opportunity to close a gap in knowledge related to the interplay among academic achievement and cognitive, motivational, pubertal, and relational processes as children move through elementary and secondary (middle school, high school) school (Pianta, 2004; Rutter & Maughan, 2002). Three distinct but related issues will be the focus of this work: (1) the nature and organization of developmental trajectories in cognitive process (specifically aspects of executive functioning), their intersection with achievement and socioemotional functioning, and their associations with experiences at home, at school, and in the community; (2) the role of experience in families, at school, and with peers at key periods of schooling in establishing and altering trajectories of achievement from school entry to the middle of high school; and (3) the nature of cumulative experiences in school (both instructionally and socially), alone and in interaction with experiences at home and in the community, and extent to which they contribute to achievement and cognitive functioning in middle adolescence. If indeed the work produced by this study that has been summarized in this chapter reflects a contribution to the understanding of development and education, then analysis of the next waves of data present an even more promising opportunity.

Acknowledgments This study was directed by a steering committee and supported by the National Institute of Child Health and Human Development through a cooperative agreement (U10), which calls for scientific collaboration between

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the grantees and the NICHD staff. Participating investigators, listed in alphabetical order, are Jay Belsky, Birkbeck University of London; Cathryn BoothLaForce, University of Washington; Robert Bradley, University of Arkansas, Little Rock; Celia A. Brownell, University of Pittsburgh; Margaret Burchinal, University of North Carolina, Chapel Hill; Susan B. Campbell, University of Pittsburgh; K. Alison Clarke-Stewart, University of California, Irvine; Sarah L. Friedman, CNA Corp., Alexandria, Virginia; Kathyrn Hirsh-Pasek, Temple University; Renate Houts, Research Triangle Institute, Research Triangle, North Carolina; Aletha Huston, University of Texas, Austin; Jean F. Kelly, University of Washington; Bonnie Knoke, Research Triangle Institute; Nancy Marshall, Wellesley College; Kathleen McCartney, Harvard University; Fred Morrison, University of Michigan; Marion O’Brien, University of North Carolina, Greensboro; Margaret Tresch Owen, University of Texas, Dallas; Robert Pianta, University of Virginia; Wendy Robeson, Wellesley College; Susan Spieker, University of Washington; Deborah Lowe Vandell, University of California, Irvine; and Marsha Weinraub, Temple University. We express our appreciation to the study coordinators at each site who supervised the data collection, the research assistants who collected the data, and especially the families and childcare providers who welcomed us into their homes and workplaces and cooperated willingly with our repeated requests for information.

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THE ROLE OF MORPHOLOGY IN READING AND SPELLING

Monique Sénéchal and Kyle Kearnan DEPARTMENT OF PSYCHOLOGY, CARLETON UNIVERSITY, OTTAWA, ONTARIO K1S 5B6, CANADA

I. II.

INTRODUCTION THE MORPHOLOGICAL STRUCTURE OF LANGUAGES

III.

MORPHOLOGICAL KNOWLEDGE A. MORPHOLOGICAL ANALYSIS B. TYPES OF MORPHOLOGICAL KNOWLEDGE C. MORPHOLOGICAL REPRESENTATIONS AND ACCESS

IV.

MORPHOLOGICAL KNOWLEDGE AND READING A. MORPHOLOGICAL EFFECTS IN READING B. READING DIFFICULTIES C. INTERVENTION STUDIES

V.

MORPHOLOGICAL KNOWLEDGE AND SPELLING A. MORPHOLOGICAL EFFECTS AND SPELLING B. MORPHOLOGICAL AND PHONOLOGICAL TRANSPARENCY C. MORPHOLOGICAL SPELLING STRATEGIES

VI. MORPHOLOGICAL AWARENESS A. MORPHOLOGICAL AWARENESS AND READING B. MORPHOLOGICAL AWARENESS AND SPELLING C. MORPHOLOGICAL AWARENESS AND VOCABULARY D. MORPHOLOGICAL AWARENESS AND PHONOLOGICAL AWARENESS E. INTERVENTION STUDIES VII. SUMMARY AND CONCLUDING REMARKS REFERENCES

I. Introduction In more than 100 years of research on the acquisition of literacy, we have made considerable progress in understanding the underlying processes and associated linguistic skills that help children learn to read and write successfully. Yet, the best models of reading and spelling explain, on average, only 70% of the variance. Hence, our understanding of the processes and skills that account for the large and stable individual differences in literacy skills is still far from complete.

297 Advances in Child Development and Behavior R.V. Kail : Editor

Copyright © 2007 Elsevier Inc. All rights reserved.

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We are nonetheless making important progress. The abundant research on the role of children’s awareness of the phonological structure of spoken languages has convincingly demonstrated that children who are better able to manipulate the sounds within languages make faster and greater gains in learning the alphabetic principle (Ehri, 2005; Ehri et al., 2001). Since the 1980s, researchers have examined the contribution to literacy of another linguistic skill, children’s knowledge and awareness of the morphological structure of spoken language, that is, their awareness that words may contain smaller units of meaning. It is not surprising that morphology has become of interest given that many orthographies such as those of English and French not only code the phonological structure of spoken language, but also mark morphological information. Young children can exhibit quite sophisticated knowledge of morphology. For example, the French-speaking 5-year-old daughter of the first author, when asked where a mouton (sheep) lives, responded “in the moutonnerie” (rather than the bergerie) and further responded that a vache (cow) lives in the vacherie (rather than the étable). Whether this type of early sensitivity to morphological structure plays a role in acquiring more explicit knowledge about morphology as well as in literacy acquisition is still being debated. In this chapter, we present experimental and correlational evidence that shows that morphological knowledge can help children to read and spell words.

II. The Morphological Structure of Languages Language theorists define morphemes, the building blocks used to create words, as the smallest units of meaning in a language. Morphologically complex words are produced by attaching inflectional or derivational forms to base forms. Morphemes are said to be bound when they have no lexical status, as in the case of prefixes and suffixes. In contrast, free morphemes have an independent lexical entity such as in base words. In many languages, more than one prefix or suffix can be attached to the beginning or end of base forms. For example, the word purifying consists of the attachment of an inflectional suffix -ing to a derivational suffix –ify, which, in turn, is attached to the bound morpheme pur (Carlisle, 2000). In the remainder of this section, we compare and contrast inflectional and derivational morphology. Inflections are suffixes that mark grammatical information such as the tense and person of verbs (play/plays/played/playing). In addition, inflections mark the plural form of nouns (hat/hats) and the comparative relations among adjectives (easy, easier, easiest). As such, inflections deal with the syntax of language rather than differences in meaning, are largely dependent on rules, and consist of a small finite class of high-frequency grammatical suffixes (Mahony, 1994). The marking of plural in English and French, for example, is accomplished most often by attaching the inflectional suffix -s to

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nouns. In French, the feminine form is most often obtained by the addition of the morpheme -e to adjectives (petit/petite, brun/brune, and lourd/lourde). Unlike inflectional morphemes, derivational morphemes change the meaning of base words and can, therefore, change the word class of the derived word (help/helpless). Derivational morphemes consist of a large class of affixes for which the rules of application are sometimes difficult to abstract. Indeed, the acquisition of derivational morphology is further complicated because not all affixes are equal in their effect on the pronunciation of base forms. For example, English orthography includes two types of suffixes: neutral and nonneutral suffixes. Neutral suffixes attach directly to base words such that removal of the derivational suffix results in the base word (Tyler & Nagy, 1989). Attaching neutral suffixes such as -ment, -ness, -er, and -ize to base words, children can create new words such as pavement, sadness, skier, and regularize. The resulting words are usually transparently related to the base words and typically do not change the pronunciation of the base words. As such, word formation using neutral suffixes should be relatively easy and frequently used to create new words in a language. In contrast, nonneutral suffixes often attach to bound morphemes instead of free morphemes (i.e., words) and tend to produce phonological changes in stress or vowel pronunciation in the stem, as in festive and festivity. Other nonneutral suffixes include -ify, -ous, -ion, and -ive. Given the properties of nonneutral suffixes, children may have difficulty recognizing the links between root words and derivatives (e.g., Jones, 1991). Because a great number of affixes can be attached to a single base word, learning derivational morphemes can be problematic for a number of reasons (Carlisle, 1988; Derwing, 1976). First, the construction of derived words from an original base word does not follow a consistent pattern. As illustrated by Carlisle, two similar words like terror and horror can share two similar derived forms such as terrible and horrible and terrify and horrify. But there is a terrorize and no horrorize, and a horrid and not a terrid. Second, the range of affixes available to the user makes learning the proper derived forms difficult (the endings -ity, -ment, -ness, -ence, and -th are just a few examples). Third, differences in meaning between the same suffixes used for different words are often difficult to learn (-ful can have two different meanings as used in cupful and helpful). And last, derived forms can undergo large shifts in meaning from their original form, such that their relation to this form can seem remote (apply and appliance). Given the complexity of derivational morphology compared to inflectional morphology, it is not surprising that children master most inflections before they reach formal schooling, but they will not experience important growth in derivational knowledge until receiving 3 to 4 years of formal schooling (Selby, 1972). That is, most learning about morphology occurs after children have had sufficient reading experience to build an orthographic lexicon. This raises the possibility that exposure to regular orthographic patterns can help

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children acquire knowledge about morphemic structure, which, in turn, may facilitate fluent reading.

III. Morphological Knowledge At least three processes are involved in learning about morphology: rote memorization, analogy, and combination (MacWhinney, 1978). Rote learning involves memorizing words without parsing them into constituent morphemes and is used for learning both regular and irregular forms (e.g., oxen). Imitation is viewed as a form of rote learning. The second mechanism, analogy, consists of extrapolating the morphophonology of a known word to new items (e.g., going from bugs to obtain wugs). And finally, combination occurs when the child creates words by combining separate morphemes. Although each process has received more theoretical attention at one point or the other, MacWhinney makes a convincing case that all three processes are used during language acquisition, but that analogy will be used when rote and combination fail. MacWhinney demonstrates clearly that these processes coexist in each of the seven languages that he examined. In addition to the linguistic processes described by MacWhinney, other dimensions of children’s morphological knowledge have been documented. In the next three subsections, we describe in greater depth how children analyze the morphological structure of words, what types of knowledge are necessary to understand the construction of multimorphemic words, and how multimorphemic words are represented in memory. A. MORPHOLOGICAL ANALYSIS Children seem able to use strategically the morphological structure of words to make inferences about the meaning of unfamiliar words. Anglin (1993) asked first, third, and fifth grade children to explain the meanings of words that were morphologically either simple (closet) or complex ( forgotten, knotless, competitive) and then use them within a sentence. Children’s knowledge of morphologically complex words grew from grade 1 to 3 and from 3 to 5. Most interesting, however, is that children in grades 3 and 5 were likely to use morphemic constituents of already known words to aid them in the search for meanings of unfamiliar words but grade 1 children did not. Morphological analysis of this type, therefore, allows children to make inferences about the meaning of morphologically complex words. Similarly, when children are given the definition of morphologically complex words such as treelet (a small tree), they can decompose other nonwords such as riverlet into morphemes when attempting to define them (Carlisle & Fleming, 2003).

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Morphological analysis presupposes some knowledge of affixes. To acquire this knowledge, children may rely on an affix discovery principle to help deconstruct morphologically complex word forms. The affix discovery principle is a two-stage process by which children come to extract knowledge about the meaning and syntactic value of affixes (Schreuder & Baayen, 1995). In the first stage, similar forms are detected; for example, the pattern -er is detected from words like baker and dancer. The second stage involves the creation of a concept node for the affix (e.g., -er) that will be activated whenever similar forms are encountered. With increased exposure to similar forms, the concept node also includes both semantic and syntactic information (-er starts to represent one who _____). This allows children to derive meaning for words that are similar in morphological structure (also see Leong, 2000). Evidence for the extraction of information about the meaning of affixes comes from young children’s construction of neologisms that include appropriate use of specific affixes as in the moutonnerie and vacherie examples given previously. Still unresolved, however, is an explanation that accounts for the appearance of the affix discovery principle. One could make an analogy to the verbal behavior of very young children (Marchman & Bates, 1994) to argue that children need to have acquired a critical mass of words that share similar affixes before the storing of individual words becomes inefficient and, consequently, results in parsing words into constituent morphemes, which, in turn, may be used to construct new words as well as to make inferences about word meanings. Such a model could be used to make hypotheses about the order of acquisition of affixes given their productivity. That is, affixes that are more productive should be acquired first. A full test of this hypothesis remains to be conducted. Analyzing the morphological structure of words necessarily implies that children will segment words into constituent morphemic units. It is, therefore, of interest to document children’s ability to decompose words into morphemic units. Older children decompose words more accurately than do younger children (Freyd & Baron, 1982; Tyler & Nagy, 1989; Wysocki & Jenkins, 1987). When asked whether words such as silly and hilly can be decomposed, third graders were found to be successful 71% of the time, whereas first graders were successful only 57% of the time (Carlisle & Fleming, 2003; also see, Rubin, 1988). In addition, Carlisle (1988) found that grade 8 students had not fully acquired knowledge of the more complex transformations between base and derived forms or even some of the simple suffix addition rules, even though there are significant improvements between grades 6 and 8. The pattern of increased morphological knowledge throughout the elementary years raises the issue of whether this pattern is due to greater accumulated lexical knowledge or greater exposure to orthographic patterns that make it easier to extract common orthographic patterns across related forms (Pacton, Fayol, & Perruchet, 2005). Along this line, examination of the reading materials available in

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middle schools shows that approximately 60% of new words in books are derived forms that are semantically transparent (Nagy & Anderson, 1984). At the same time, extracting common orthographic patterns alone might not be enough to produce growth in morphological knowledge because common orthographic patterns might not reflect morphological relations (e.g., bear, beard; Carlisle, 2000).

B. TYPES OF MORPHOLOGICAL KNOWLEDGE At least three types of knowledge are involved in producing and recognizing morphologically complex words (Tyler & Nagy, 1989). Children should know about (a) the relations between base and derived forms, (b) the syntactic changes caused by attaching affixes, and (c) the constraints that guide which types of affixes are attached to which base forms. Clark and Cohen (1984) showed that 4- and 5-year-olds had some implicit knowledge about the relation between verbs and the agentive suffixes -er and -ist. In addition, other evidence shows that children can demonstrate explicit relational knowledge in the elementary grades when the base form is a familiar word, but may not be able to apply this knowledge to rare base forms until later in middle school (Anglin, 1993). Application of this knowledge seems to be sensitive to the familiarity of the base forms. The second type of knowledge concerns the syntactic functions of suffixes; for example, that the addition of the agentive -er changes a verb to a noun as in play/player. Children often have difficulty defining explicitly the syntactic value of derivational suffixes (Wysocki & Jenkins, 1987), but seem able to use derivational suffixes correctly (Sterling, 1982). Explicit morphological knowledge develops later in the elementary school years. For instance, only 10% of first graders and 36% of third graders used the word stillness in a sentence that took into account both the semantic and the grammatical role of the suffix -ness (Anglin, 1993). The third type of knowledge concerns an awareness of the constraints that guide the combination of stems and suffixes. That is, with sufficient exposure to spoken, and possibly to written, languages, children gain knowledge about which types of suffixes attach to which word classes. For instance, knowing that -ly attaches to verbs and not nouns; that the agentive suffix -er can be attached to verbs, but not adjectives; and that the suffix -ness can be attached to adjectives, but not to verbs. Tyler and Nagy (1989) proposed a model of acquisition in which explicit knowledge of distributional constraints should be acquired after the other two types of knowledge because it presupposes that children can identify the relations between base and derived words as well as have some knowledge of the syntactic function of affixes. In fact, Tyler and Nagy report an increase with grade of children’s knowledge of distributional constraints: older

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children indicated more frequently that they knew the meaning of experimental words that obeyed distributional constraints (e.g., dreamful) compared to words that were ill formed (e.g., repeatize). Grade 4 children indicated that they knew the meaning of approximately 25% of the well-formed experimental words, grade 6 children 42%, grade 8 children 45%, and college students 58%. Although Tyler and Nagy (1989) provide a complete description of the types of knowledge necessary to recognize and produce multimorphemic words, they noted that most of the research on children’s understanding of derivational morphology had concentrated on how children recognize the relation between base and derived words. As we reviewed the research literature up to 2006, we found this to be still the case.

C. MORPHOLOGICAL REPRESENTATIONS AND ACCESS How adults and children represent and access morphologically complex words in their lexicon is not yet fully understood. The main issue concerns whether morphemic units are represented lexically and centers on two competing hypotheses, namely, the decomposition hypothesis and the full-listing hypothesis. According to the decomposition hypothesis, the meanings of morphologically complex words are processed through their individual morphemic units. For example, the two morphemes of cheerful are represented separately. Within this framework, base words and suffixes/prefixes are stored individually in the lexicon and, consequently, activated separately when accessing the meaning of a particular word. According to this view, morphology should affect processing. In contrast, the full-listing hypothesis suggests that morphologically complex words have their own representation in memory and, consequently, morphology should not affect lexical access. In addition to these two separate hypotheses, interactive models that combine both views are also proposed. For instance, Taft (2003) argued convincingly that morphemic units that are known in spoken language are represented internally and affect processing, but morphology does not affect processing for unfamiliar words or words for which morphemic units are not identified. Accordingly, both the whole word and the word’s morphemic units play a role in processing (Colé, Ségui, & Taft, 1997; Niswander, Pollatsek & Rayner, 2000). In fact, extant research findings with adults suggest that the morphemic structure of words can facilitate processing even when the phonological and orthographic features of derived words are not transparently linked to base words (e.g., Nagy et al., 1989; Schreuder, Burani, & Baayen, 2003). The models described previously suggest that morphological information is treated at a semantic level, but morphological parsing might occur earlier in the process of word recognition, that is, at the level of the orthography. To explore this

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possibility, Christianson, Johnson, and Rayner (2005) used a priming paradigm to test the hypothesis that reading derived words (e.g., boaster) is sensitive to the morphemic units in the words. Specifically, they hypothesized that reading might be hampered when primes included letter-sequence transpositions across morphemic boundaries (boasetr) compared to other transpositions such as across syllables (boatser). Indeed, skilled readers were slower at reading derived words that end with the agentive morpheme -er (boaster) when primes included letters transposed across morphemic boundaries (boasetr) compared to primes with letter transposition elsewhere in the word (boatser) or correctly spelled primes (boaster). The effect was specific to multimorphemic words because skilled readers were not slower at reading pseudo-morphemic words such as bluster when primes included letter transpositions across the presumed morphemic boundary as opposed to primes with letter transpositions across syllables. In this experiment, the bigram frequency of words, primes, and pseudo-words was controlled and, consequently, the effect of morphology cannot be entirely explained by alternative models of implicit learning of orthographic regularities (cf. Pacton et al., 2005).

IV. Morphological Knowledge and Reading In addition to understanding what provokes growth in morphological knowledge, researchers want to understand whether morphological knowledge can help children read and spell. At one end of the theoretical debate on whether morphology plays a causal role in reading and spelling, theorists posit that the processing of morphological units aids the retrieval of lexical entries (including orthographic patterns) during reading and spelling. At the other end of the debate, theorists argue that orthographic structure is processed rather than morphological structure. That is, the cognitive system is such that children extract orthographic regularities from text and use those regularities to aid word recognition during reading (Venezky, 2004). The first view posits that linguistic processes are involved, whereas the second argues that perceptual learning accounts for the differences in ease of processing. In the next three subsections, we examine: (a) whether children show some sensitivity to morphology when they read, (b) whether children with reading difficulties have weaker morphological knowledge, and (c) whether intervention research provides additional support for a causal role of morphological knowledge in literacy. A. MORPHOLOGICAL EFFECTS IN READING Three questions have been examined in the developmental literature: first, whether morphology facilitates word reading; second, whether the frequency of base and derived words affects performance; and third, whether the phonological

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transparency of derived words affects performance. The first question addresses the role of morphology in general, whereas the two remaining questions examine whether specific features of multimorphemic words affect reading performance. Each of these questions and the related findings are described in turn. If, indeed, children represent morphemes in addition to orthographic sequences during reading acquisition, these morphemic representations may help children read multisyllabic words. Consider that the representation of the suffix -tion could help one read a variety of unfamiliar words, such as invention, persecution, creation. In contrast, if children extract letter patterns only, then one should not find differences between reading words that have similar characteristics, except when one is a derived word (e.g., hilly) and the other is not (e.g., silly). Carlisle and Stone (2005) examined this question and found that children in grades 2–6 read derived words (e.g., mower) more accurately then pseudo-derived words (e.g., tower) and that the difference in performance could not be accounted for by word length or frequency differences within pairs (e.g., shady–lady). Although the effect was small, it was reliable. This pattern was replicated in Dutch, a language that is more transparent than English and that frequently includes prefixes in polysyllabic words (Schreuder & Baayen, 1994). In two studies, Verhoeven, Schreuder, and Haarman (2006) showed that grade 3 and 6 children as well as adults were more accurate and/or faster at reading words that included real prefixes compared to reading words with pseudo-prefixes. Consistent with linguistic analyses of Dutch, they also found larger effects for more frequent prefixes as opposed to less frequent prefixes. The findings described suggest that, like adults, elementary school children show some sensitivity to the morphemic structure of words. Another issue examined is whether reading processes are affected by the frequency of base and derived forms as well as the size and the average frequency of families of morphologically related words. The reasoning is as follows. Efficient and accurate reading requires access to well-specified orthographic representation of words, and these orthographic representations develop through repeatedly reading the same words (Ehri, 2005; Reichle & Perfetti, 2003). It follows that words that are read more frequently might have more accurate orthographic representations, which, in turn, can increase the speed and the accuracy with which these words are read. The facilitative effects of frequency, in fact, are well established in the adult word-recognition literature. Because derived forms necessarily overlap entirely or in part with base forms, reading derived forms should activate and reinforce the representation of the base. Moreover, word families for which there are numerous derivatives could result in more exposure to morphemic units within that family than word families for which there are few derivatives. Finally, the frequency of derived words themselves can also affect reading. Research with adults suggest that the frequency of base forms is more

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important in predicting reading speed than is word-family size or frequency (e.g., Nagy et al., 1989), although word-family size and frequency also affect performance (for a discussion, see Reichle & Perfetti, 2003). Research with elementary school children reveals that children are more accurate: (a) when reading multisyllabic derived words from large families than from small families, (b) when reading derived words for which the average word frequency in the family was high compared to low, and (c) when reading derived forms that have a high frequency compared to derived words with a low frequency when both types of words have highly frequent base forms (Carlisle & Katz, 2006). These interesting findings are consistent with a view of reading acquisition that is sensitive to the frequency of exposure to words in written texts. In addition to the facilitative effects of frequency, the facilitative effects of transparency within word families have received attention in the developmental literature. As described previously, derived words vary in the degree with which they preserve clear transparent relations with base forms, and it becomes of interest to assess whether the degree of transparency between derived and base forms affects reading performance. Of special interest is whether words for which the addition of a suffix results in a shift in the phonology of the base word (e.g., colony/colonial) are more difficult to read than are derived words that maintain a transparent phonological relation (e.g., classic/classical). Indeed, children seem to have more difficulty reading derived words that are not phonologically transparent compared to transparent derived words (Carlisle, 2000; Mann & Singson, 2003). In this research, however, phonological shifts are sometimes confounded with orthographic shifts or with semantic opacity. That is, the addition of the suffix also modifies the orthography of the base word (e.g., mature/maturity) or the semantic relation between base and derived form is not clear (e.g., apply/appliance). In a subsequent study, however, Carlisle and Stone (2005) included derived words that were phonologically opaque but orthographically and semantically transparent (e.g., final/finality) and still found that children in grades 3–6 as well as adolescents from grade 7 to 9 read phonologically transparent derived words more accurately than phonologically opaque derived words. The research on reading reviewed here is consistent with the notion that morphology does play a role in reading, although that role seem to interact with other features of the language such as frequency, phonology, and orthography. Most of the evidence presented so far concerns alphabetic languages, but if universal properties are to be considered, then one has to consider other types of orthographies such as Chinese. The Chinese script is described as morphosyllabic because each character in the orthography represents both a morpheme and a syllable at the same time. In their work on Chinese reading, McBride-Chang and her colleagues clearly show that morphological knowledge plays a larger role than phonological processing during reading

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acquisition (e.g., McBride-Chang et al., 2003, 2005a, 2006). This interesting pattern suggests that the relative contribution of morphology to literacy may depend on the characteristics of the written language. This possibility is examined further in the section on spelling. In sum, the limited developmental research on reading shows that children are sensitive to morphological features during reading and that specific morphological features affect performance. In the next sections, we examine whether morphological knowledge is weaker in children with reading difficulties and review intervention studies testing whether improving children’s morphological knowledge will improve reading comprehension.

B. READING DIFFICULTIES A number of studies have examined whether morphological knowledge is weaker in children who are at risk of developing reading difficulties as well as children with identified reading difficulties. Nagy et al. (2003) found that measures of morphological knowledge were related to reading outcomes for grade 2 children at risk for reading deficits and for grade 4 children at risk for writing deficits. Furthermore, morphological awareness made a unique contribution to reading comprehension for the grade 2 sample after controlling for vocabulary as well as phonological and orthographic awareness. This pattern, however, was not replicated for measures of word reading, decoding, or spelling. Therefore, one could argue that the contribution of morphological awareness is constrained to sentence and text integration. This interpretation must be nuanced because the unique role of morphological awareness in reading comprehension was not replicated in the sample of grade 4 at-risk writers even though the correlation between morphological awareness and reading comprehension was higher in grade 4 (r ⫽ 0.80) than it was in grade 2 (r ⫽ 0.69). The overall pattern of findings is somewhat difficult to interpret because of the potential confound caused by presenting visually the stimuli for the morphological awareness tasks. Specifically, children were looking at a written version of each test item while the examiner read them aloud. In this study, children’s morphological awareness performance may partly reflect their literacy skills, especially so in grade 4. Poor readers have difficulty reading multimorphemic words in general (Carlisle & Stone, 2005) and particular difficulty reading words for which the affixation is not phonologically and orthographically transparent with the base word (Berninger et al., 2003; Carlisle & Katz, 2006; Carlisle & Nomanbhoy, 1993; Fowler & Liberman, 1995; Leong, 1989). Children with reading difficulties also have difficulty with written tasks of inflectional and derivational morphology compared to younger children who are matched on reading and spelling age (Carlisle, 1987; Carlisle, 1996; Hauerwas & Walker, 2003). For instance,

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Carlisle (1987) found that grade 9 dyslexic children did not rely on the relation between some derived and base forms (magic and magician) when they spelled because they produced errors based on their knowledge of phonology (magition, magistion, magishan). Also, dyslexic students were more likely to disregard the morphological structure of derived words in their spellings than normal-reading grade 4 children. Although the accumulated evidence would suggest that children with reading difficulties also have difficulty processing morphological information orally, Egan and Pring (2004) argue against an oral language difficulty. They reported that dyslexic children did not show deficits in processing inflected verbs orally compared to normally developing younger children of the same reading age, but dyslexic children were slower at reading and less accurate at spelling regularly inflected verbs than were the same reading-age children. In contrast, other researchers have found that some dyslexic children do have oral language impairments that include morphological processing difficulties (e.g., Joanisse et al., 2000). From the studies described in this section, it is clear that processing morphological information is more difficult for children with reading difficulties. In all studies, morphological information affects performance, although there is still some debate as to whether the weaknesses exhibited by reading-disabled children are limited to written language or extend to spoken language.

C. INTERVENTION STUDIES Intervention studies are necessary to demonstrate the causal role played by morphological knowledge in reading. The intervention studies conducted to date have tested whether increasing children’s morphological analysis increases their reading comprehension skills. As described, these studies typically show specific benefits of instruction, but have yet to demonstrate clearly more general and long-lasting effects. Several studies have tested whether training children to use morphological analysis would enhance their reading comprehension. The idea underlying this research is that children with strong morphological analysis skills might be better able to infer the meaning of unfamiliar words and, consequently, understand written texts better. The results of some of these studies show that children can learn about morphological analysis and that there may be immediate benefits on some outcomes, but that students have difficulty generalizing to uninstructed suffixes as well as continuing to use morphological analysis over time. Otterman (1955) found that teaching grade 7 students about prefixes and roots during thirty 10-min lessons helped students’ spelling skills compared to controls, but there were no beneficial effects on general vocabulary or reading comprehension. Similarly,

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Freyd and Baron (1982) failed to find benefits of suffix instruction (five 45-min lessons) on grade 8 students’ knowledge of morphologically complex words. In contrast, Graves and Hammond (1980) reported that grade 8 students who received three 20-min lessons about suffixes could use their knowledge to infer the meaning of transfer words that included the same suffixes. A similar finding was obtained by Tomesen and Aarnouste (1998) in a sample of grade 4 Dutch children who received twelve 45-min lessons. Baumann et al. (2002) found that training grade 5 students during twelve 50-min sessions on morphemic analysis either alone or in conjunction with instruction on using contextual information did enhance children’s ability to extract word meanings as well as analyze uninstructed words into morphemic components compared to control students. Although the latter three studies show benefits of intervention, there are limits on these effects. In the Baumann et al. study, for example, the benefits were short lived: 5 weeks after the intervention, the groups no longer differed. A different limit was shown in the Graves and Hammond as well as the Baumann et al. study; here, the beneficial effects did not generalize to reading comprehension. Bauman et al. argue that it might be unrealistic to expect that short-term interventions would increase students’ general reading comprehension given that factors other than vocabulary are clearly at play during comprehension. Moreover, the reading comprehension measures might not be sensitive to the specific effects of morphological analysis. Nevertheless, morphological analysis can be successfully taught, and it is now necessary to understand better the instructional conditions that will sustain the use of morphological analysis over time in order to demonstrate pervasive effects on reading comprehension.

V. Morphological Knowledge and Spelling The rules of word formation are very clear and phonologically transparent in some languages such as Finnish, but they are less clear in languages such as English and French. The English orthography maps onto the morphophonological structure of the language because some spelling patterns represent the etymology of a word, or its morphology, in addition to mapping phonemes onto corresponding graphemes. Consider that a child who understands that the regular past tense of verbs is marked with -ed will be able to overcome the phonologically inconsistent /t/ ending of verbs like dressed, kissed, and stopped. In the case of French, children will be able to mark the plural of nouns and present-tense verbs for which the plural has no phonological marking as in the sentence ils dansent, which is phonetically equivalent to the singular form il danse. In this section, we examine the role of morphology in spelling. The research on spelling has focused on three broad issues: (a) whether children are sensitive to morphological information when they spell, (b) whether the

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morphological transparency of the orthography affects spelling performance, and (c) whether children explicitly use their morphological knowledge to help them spell. Each issue is described in turn.

A. MORPHOLOGICAL EFFECTS AND SPELLING Young children seem sensitive to morphological information when they attempt to spell words. Treiman and Cassar (1996) found that kindergarten and grade 1 children’s omissions of certain consonants was affected by the morphological status of the letters, as children were more likely to omit the letter r in one-morpheme words (Mars and beard) then in two-morpheme words (bars and stored). Similarly, children were less likely to spell the /n/ sound correctly in words like brand than in words like tuned. Children’s spelling accuracy of multimorphemic words and the frequency with which they use morphologically complex words in their writing increase with grade level. For instance, grade 3 children were significantly more accurate in spelling morphologically complex words in their story writing than were grade 2 children. Moreover, grade 3 children used significantly more morphologically complex words overall than their second grade counterparts (Carlisle, 1996). Green et al. (1995) noted similar grade-level changes in the narratives produced by grade 3 and 4 children. In addition, Nunes, Bryant, and Bindman (1997a) showed that 6- to 11-year-old children acquire gradually the spelling of the regular past tense in verbs. Initially, children spell all past tense verbs phonetically, then use the -ed for verbs but for nonverbs as well (e.g., writing “soft” as “sofed”), before they master the rule. Some rules of morphology, however, are more difficult to master and, consequently, are acquired later. For English-speaking children, the mastery of morphological knowledge of possessive nouns (e.g., I saw the boy’s sail) is particularly difficult even for 11-year-old children. Hence, the correct application of suffix rules may not be fully mastered by the eighth grade, even though significant improvement are made between the sixth and the eighth grade (Carlisle, 1988). Spelling of derivatives has also been studied by examining children’s ability to use base forms to spell derived forms. Using a paradigm akin to priming in visual word recognition, Deacon and Bryant (2005) found that 7- to 9-year-olds were sensitive to the derivational relations in their spellings. In the study, children spelled words that would complete sentences that included a clue to the spelling of the derived word. For example, children heard the target word objection and were to spell this target to fill in the blank in the written sentence I object to his main _____. In this case, the clue in the sentence context was the base form object. In this study, children were more accurate at spelling derived words such as payment when the base form pay was included in the sentence

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context and were less accurate at spelling monomorphemic words such as pigment when a pseudo-base such as pig was used in the sentence context.

B. MORPHOLOGICAL AND PHONOLOGICAL TRANSPARENCY The extant research suggests that the role of morphological knowledge in spelling is closely linked to the degree of phonological transparency of the orthography. This is illustrated in this section by contrasting the results obtained in Finnish and French, two languages that differ in phonological transparency. Languages such as Finnish are interesting because they are richer morphologically than English but, in contrast to English, morphemes in Finnish are always spelled exactly as they are pronounced (Vannest et al., 2002). Therefore, in the beginning stages of spelling acquisition in Finnish, morphology may play a relatively small role because the very transparent orthography does not pressure the speller to use other linguistic information outside the phonological structure of the language. Indeed, Lehtonen and Bryant (2005) found that Finnish children in grades 1–3 used significantly more phonological rules than morphological knowledge in their spellings. Only at the end of grade 3 did morphology appear to affect children’s spelling development. In contrast to transparent languages like Finnish, the French written language represents aspects of morphology that are not represented phonologically. For instance, inflected words and root words often end with silent consonants that indicate morphological information. Consider that the plural is most often marked with a final silent -s in nouns and a silent -nt in regular verbs, and the silent final consonant in certain nouns marks the relation with derivatives such as derived verbs (e.g., chant/chanter; repos/reposer). Hence, the predominantly silent morphology means that children must learn to spell words correctly without an oral reference (Alegria & Mousty, 1996; Cormier & Kelson, 2000; Fayol, Totereau, & Barrouillet, 2006; Pacton & Fayol, 2003; Totereau, Thevenin, & Fayol, 1997). In research on marking the plural of nouns (-s) and verbs (-nt), Fayol and his colleagues observed that grade 1 children frequently failed to mark the plural (Fayol, Hupet, & Largy, 1999); that when spelling homophones, children overgeneralize the use of -s to verbs and the use of -nt to nouns (Totereau, Barrouillet, & Fayol, 1998); and that even skilled spellers are easily disrupted in their subject–verb agreement (Fayol, Largy, & Lemaire, 1994). These findings demonstrate the increased difficulty of languages in which there is a mismatch between phonological and morphological information. Given the morphophonological structure of French (Clark, 1985), one can expect an increased role for morphological knowledge in spelling correctly. Indeed, French children’s sensitivity to morphological information facilitated the choice of appropriate silent endings in grades 2 and 4 (Sénéchal, 2000; Sénéchal,

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Basque, & Leclaire, 2006) as well as appropriate homophonic endings in grades 2 and 3. In French the phoneme /o/ can be spelled o, ot, au, or eau, but only the grapheme eau marks the inflection for the masculine diminutive. Pacton et al. (2005) found that children were more likely to include the grapheme eau in their spelling of pseudo-words when the sentence context clearly indicated that the pseudo-word was a diminutive (A little /vitar/ is a /vitaro/ ) as opposed to when the sentence context did not indicate a diminutive form (A tall /vitar/ is a /vitaro/ ). These morphological effects, however, interacted with the graphotactic probability of the final two graphemes, such that children spelled /o/ with the grapheme eau less frequently when the graphotactic probability was low (i.e., f rarely precedes eau) than when it was high (i.e., v frequently precedes eau). Taken together, these results suggest that children integrate information from a variety of sources when they spell.

C. MORPHOLOGICAL SPELLING STRATEGIES The research described so far in this section presumes that children acquire knowledge about morphology through exposure to written texts and that the extraction of morphemic features does not require explicit processing, but may occur implicitly (e.g., Pacton et al., 2005). Other research, however, has found that children can use the morphological relations between words strategically and explicitly to help them spell words accurately. By thinking of the morphological relations among words, children can choose the correct spelling from other possible spelling alternatives. Consider the case of the silent letters in the French orthography. For children to spell accurately the silent t in chant, writers can use their understanding of the link between chant and chanter to write the silent-consonant ending. A morphological strategy can help in two ways: it alerts children to the presence of a silent-consonant ending, and it allows the selection of the silent letter. Sénéchal et al. (2006) conducted two studies to examine whether children made use of morphological information when spelling French words that contain silent final consonants. They hypothesized that spelling accuracy should be linked to how deeply children had to go in the orthographic structure of words to extract the correct spelling. To test their hypothesis, they compared the spelling accuracy of three types of words, namely, phonological, morphological, and lexical words. Phonological words were those that contained consistent phoneme–grapheme patterns, whereas both morphological and lexical words ended with a silent consonant. Morphological words were defined as those for which derivatives clearly revealed the silent-consonant ending. For example, rang would be classified as a morphological word because the silent-letter g in rang can be determined by thinking of its derivative, rangée. Finally, lexical words were those for which the final-silent consonant had to be

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memorized because derivatives, if any, would not readily and clearly reveal the final-silent consonant (e.g., tabac—tabagie or tabatière). As expected, Sénéchal et al. found that words that obeyed phonological rules were the easiest to spell, and morphological words were easier to spell than lexical words. The significant advantage of morphological words over lexical words suggested that children are sensitive to the morphological structure of words. In fact, Sénéchal (2000) had previously interpreted similar findings as evidence of morphological strategy use, but this evidence is indirect at best. Children may not use morphological strategies at all, but find that orthographic representations of morphological words are easier to store in long-term memory due to the redundancy in orthographic patterns among root words and their derivatives. To verify the use of strategies, Sénéchal et al. documented whether children would report using morphological strategies and whether the reported use of morphological strategies would be linked to spelling accuracy. They found that children did report using morphological strategies and that children who reported using morphological strategies tended to spell the words correctly and, generally, to do so at the same level as children who reported using retrieval. These findings support and extend previous research that has investigated indirect evidence of the value of morphological strategy use (Carlisle, 1988; Waters, Bruck, & MalusAbramowitz, 1988). The specificity of reporting morphological strategies when spelling morphological words as well as the accuracy linked with these reports provides some converging evidence to demonstrate that children can use morphological knowledge explicitly during spelling. To summarize the findings on morphology and spelling, the research reviewed has generally shown that although most children master the oral forms of inflectional morphology by the age of 5 and although young children also show some sensitivity to morphology in their early attempts to spell, most children take 3 to 4 years of formal schooling to master the spelling of inflectional endings. In addition, the research findings presented in this section suggest that the role of morphological knowledge in spelling is closely linked to the degree of phonological transparency of the orthography. Morphological knowledge seems to play a minimal role during the acquisition phase of written languages that have transparent orthographies, but morphological knowledge seems to play a larger role for languages for which this is not the case. Finally, children do report using morphological knowledge explicitly when they spell.

VI. Morphological Awareness Morphological awareness is defined as children’s conscious awareness of the morphemic structure of words that allows them to reflect upon and manipulate individual morphemic units (Carlisle, 1995; Casalis & Louis-Alexandre,

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2000; Deacon & Kirby, 2004; McBride-Chang et al., 2005b; Nunes, Bryant, & Bindman, 2006). Morphological awareness refers to children’s linguistic insight that words can be parsed into constituent morphemes. As such, morphological awareness can be viewed as a component of morphological knowledge that is distinct from morphological analysis because morphological awareness does not presuppose children’s ability to define the meaning of morphemic units as does morphological analysis. Morphological awareness has been measured for inflections, derivations, and compounds; and most morphological awareness tasks assess children’s knowledge of the relation between a base form and a derived or inflected form. Sometimes children are asked to produce multimorphemic words (e.g., Carlisle, 1988; Nunes et al., 1997a, 1997b) or to decompose multimorphemic words (e.g., Carlisle & Fleming, 2003; Casalis & Louis-Alexandre, 2000), and sometimes they are required to make judgments about the correctness of derivatives or inflections (e.g., Ku & Anderson, 2003; Nagy et al., 2003; Nagy, Berninger, & Abbott, 2006; Rubin, 1988). Morphological awareness has been studied mostly with elementary school children (e.g., Nunes et al., 1997a), but some studies included kindergarten (e.g., Casalis & Louis-Alexandre, 2000; McBride-Chang et al., 2005b, 2006) as well as middle school children (e.g., Hauerwas & Walker, 2003). Most tasks used to measure morphological awareness include real words, but some include pseudo-words (e.g., Hauerwas & Walker, 2003; McBrideChang et al., 2005b). Finally, morphological awareness is most often assessed orally, but sometimes researchers require that children follow along as the experimenter reads the stimuli (e.g., Ku & Anderson, 2003; Nagy et al., 2003, Nagy, Berninger, Abbott, 2006). Interestingly, the extant research has almost exclusively focused on the relation between morphological awareness and literacy skills, and there is a surprising lack of studies that have examined the development of morphological awareness itself. In fact, we found only two studies that measured morphological awareness longitudinally. Casalis and Louis-Alexandre (2000) found that children’s performance on a variety of morphological tasks increased steadily from kindergarten to grade 1, but they did not report the longitudinal relations among various morphological skills. In their study, Carlisle and Fleming (2003) reported a moderately small correlation between children’s morphological decomposition in grade 1 and their morphological production in grade 3 as well as between grades 3 and 5. The surprisingly small correlation coefficients over time may reflect that growth in morphological knowledge is quite uneven during this period. The sample sizes in these studies, however, were very small. Comparisons across tasks and word characteristics have also been conducted. Derivation appears to be more difficult than decomposition, at least in grade 3 (Carlisle, 2000). This finding, however, must be interpreted in light of Casalis and Louis-Alexandre’s (2000) result that when the morphemic units are given,

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kindergarten children performed better on this modified production task than on a decomposition task. Taken together, these findings suggest that access to appropriate suffixes may be the reason that production tasks are more difficult for older children. Consistent with findings previously described for reading and spelling, children find it easier to manipulate orally phonologically and orthographically transparent words such as movement compared to words that are phonologically and/or orthographically opaque such as invention, swimmer, or production (Carlisle, 2000; Fowler & Liberman, 1995; Jones, 1991). In addition, the lexical status of words might also affect performance because Casalis and Louis-Alexandre found that kindergartners manipulated real words more easily than pseudo-words. Hence, both task demands and word characteristics affect children’s morphemic awareness performance. In the next sections, we examine in greater depth the relation between morphological awareness, reading, spelling, and other child outcomes. We also review the intervention studies conducted to assess whether training in morphological awareness enhances literacy skills.

A. MORPHOLOGICAL AWARENESS AND READING The issue addressed in this section is whether individual differences in children’s awareness of morphology accounts for differences in children’s reading. The literature reviewed is correlational in nature and it was synthesized using standard meta-analytic procedures such as adjusting correlations for sample sizes prior to calculating the mean for a class of studies (Shadish & Haddock, 1994). The advantage of using meta-analytic procedures is that they allow one to assess the degree of variability across studies and, consequently, to assess whether moderating variables can account for the interstudy variability. To be included, studies needed to report oral measures of morphological awareness and measures of reading and/or spelling, as well as reporting the correlation coefficients between morphological awareness and literacy outcomes. The focus on oral measures rather than on written measures of morphological awareness was necessary to avoid confounding reading skill with morphological awareness. Many of the reports selected also included measures and correlations for oral vocabulary and phoneme awareness outcomes, and those data were also analyzed with meta-analytic methods. Moreover, some reports included more than one study or reported data separately for different samples (e.g., Chinese and English); and in those cases the results for the different studies or samples were entered separately whenever the sample size was close to one hundred children in order to provide stable correlation coefficients. Included in the analyses were twenty-two research reports that represented data for twenty-nine independent samples. These studies, described in Table I, represent

108 60 26 101 50 19 103 48 88 74 75 106 226 40 24 98 101 217 100 100 100 115 105 115 199 112 39 152

1; 2 3; 5 1; 3 1 K to 2 1 to 3 2 to 5 2; 3; 4 3; 6; 7; 8 1; 2; 3; 4 3; 4 1; 2; 3 4; 5; 6 K to 1 9 3;4;5; 6 3;4;5; 6 K 2 2 2 k 2 K 1; 2 2; 4 4 5; 6

E E E E F F E E E E E Fi E H E E E C C-T C K E E F F F F C

MA type

Rdg

No No Yes No No Yes Yes Yes No No No Yes No Yes Yes No No No No No No No No Yes Yes No

I D I/D Both Both D I D I D Both I D I

0.56 0.38

No

Both Both D D D D D D Both I D D D

0.37 0.36 0.54 0.65 0.58

Spell

PA

0.55 0.51 0.51 0.31

0.53 0.28 0.44 0.49 0.49 0.55 0.44

0.58 0.41 0.57 0.27 0.39 0.40 0.36 0.39 0.19 0.40 0.35 0.48 0.43 0.32

Voc

0.59 0.37

0.42 0.62 0.44 0.45 0.39 0.41 0.48 0.41 0.53 0.40

0.41 0.40 0.34 0.29 0.42 0.43 0.35 0.30 0.41 0.45 0.47

0.39

0.22

Rdg, reading; Voc, vocabulary; PA, phonological awareness; E, English; F, French; Fi, Finnish; H, Hebrew; C, Chinese, Cantonese; T, Taiwanese; K, Korean; I, inflections; D, derivations.

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Brittain (1970) Carlisle (2000) Carlisle and Fleming (2003) Carlisle and Nomanbhoy (1993) Casalis and Louis-Alexandre (2000) Colé et al. (2004) Deacon and Kirby (2004) Fowler and Liberman (1995) Hauerwas and Walker (2003) Kemp (2006) Kemp (2006) Lehtonen and Bryant (2005) Leong (2000) Levin, Rapid, and Rapaport (1999) Mahony (1994) Mahony et al. (2000) Mahony et al. (2000) McBride-Chang et al. (2006) McBride-Chang et al. (2005a) McBride-Chang et al. (2005a) McBride-Chang et al. (2005a) McBride-Chang et al. (2005b) McBride-Chang et al. (2005b) Ouellette and Sénéchal (2006) Plaza and Cohen (2004) Sénéchal (2000) Sénéchal et al. (2006) Shu et al. (2006)

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TABLE I Study Characteristics and Correlation Coefficients between Morphological Awareness, Literacy Outcomes, Vocabulary, and Phoneme Awareness

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a total of 3,254 children from kindergarten to grade 9. The first question we asked was whether a statistically significant relation existed between morphological awareness and reading skills broadly defined. The mean correlation was moderate at 0.41 (CIs⫽0.37 to 0.46) and statistically significant (z⫽19.40, p⬍0.001) for the nineteen samples representing 2,021 children. The homogeneity statistic, however, was significantly different from 0, indicating that there was considerable variability across studies (Q⫽38.92, p⬍0.01). To understand whether specific variables accounted for the variability across studies, we separated the studies conducted on alphabetic languages from those conducted on nonalphabetic languages. Preliminary analyses yielded one outlier for the alphabetic languages studies (i.e., grade 2 sample from McBride-Chang et al., 2005b), and, consequently, this study was removed. The eleven remaining independent samples representing 827 children yielded a moderate association between morphological awareness and alphabetic reading (r⫽0.49, CIs⫽0.42 to 0.56, z⫽15.11, p ⬍ 0.001) that was homogeneous across studies (Q⫽16.31, p⬎0.05). Similar homogeneous results were obtained for the series of seven studies conducted by McBride-Chang and her colleagues, although the mean correlation coefficient was slightly smaller (N⫽1,089, r⫽0.37, CIs⫽0.31 to 0.43, z⫽12.68, p⬍0.001, Q⫽6.11, p⬎0.05). Furthermore, many of these individual studies have shown that morphological awareness makes a unique contribution to children’s reading after controlling for vocabulary (Carlisle, 2000; Mahony, Singson, & Mann, 2000), phoneme awareness (Carlisle, 1995; Mahony et al., 2000; Nagy et al., 2003, 2006), orthographic awareness (Nagy et al., 2003, 2006), and verbal short-term memory (Deacon & Kirby, 2004; Singson, Mahony, & Mann, 2000). Most importantly, oral morphological awareness makes a unique contribution to reading comprehension after controlling for both vocabulary and reading of morphologically complex words (Carlisle, 2000). Hence, the meta-analytic results show that morphological awareness holds a reliable and moderate relation with reading in alphabetic and nonalphabetic languages.

B. MORPHOLOGICAL AWARENESS AND SPELLING The meta-analysis also allowed us to test whether a statistically significant relation existed between morphological awareness and spelling skills broadly defined. All the studies found were conducted on alphabetic languages. The mean correlation adjusted for differences in sample sizes was moderate for the eleven studies representing 1,122 children (r ⫽ 0.46, CIs ⫽ 0.40 to 0.52, z ⫽ 26.16, p ⫽ 0.001), and for this class of studies the homogeneity statistic was not significantly different from 0 (Q ⫽ 8.13, p ⬎ 0.05). Here, too, individual studies reveal that morphological awareness makes a unique contribution to spelling after controlling for age (Nunes et al., 1997a, 1997b; Sénéchal, 2000), intelligence (Nunes et al., 1997a, 1997b), previous measures of spelling (Nunes et al., 1997a, 1997b)

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or spelling of regular words (Sénéchal, 2000; Sénéchal et al., 2006), vocabulary (Fowler & Liberman, 1995; Sénéchal, 2000), phoneme awareness (Sénéchal, 2000), and naming speed (Plaza & Cohen, 2004). In sum, the findings presented in this and the previous section show that morphological awareness has a robust moderate relation to reading and spelling, that this relation is similar in magnitude for reading and spelling in alphabetic languages, and that there is some limited evidence for a longitudinal relation between morphological awareness and literacy outcomes. It is also clear that we have yet to understand whether there is a single construct that underlies the various morphological skills that children exhibit over time. Certainly, Sénéchal et al. (2006) found a robust relation between morphological awareness and the frequency with which children reported using morphological strategies to spell.

C. MORPHOLOGICAL AWARENESS AND VOCABULARY We raised the hypothesis earlier that children need to have acquired a critical mass of words that share similar affixes before the storing of individual words becomes inefficient and, consequently, results in parsing words into constituent morphemes. It is therefore reasonable to expect an association between morphological awareness and general vocabulary. Indeed, vocabulary knowledge has been found in a variety of studies to be associated with morphological awareness as indicated in Table I. These data allowed us to assess the magnitude of the relation between vocabulary and morphological awareness. The mean correlation was moderate for the nineteen studies representing 2,556 children (r ⫽ 0.48, CIs ⫽ 0.44 to 0.52, z ⫽ 26.41, p ⬎ 0.001). The homogeneity statistic was not significantly different from 0, indicating a certain stability across studies (Q ⫽ 23.41, p ⬎ 0.05). Although correlations do not indicate the direction of the relation, the data are consistent with our view that initial vocabulary size is important to morphological awareness. The direction of the relation may change over time such that children with better morphological awareness skills may more rapidly make gains in vocabulary. That is, morphological awareness skills in conjunction with morphological analysis may explain the rapid vocabulary growth that occurs between the ages of 7 and 12 (Anglin, 1993). To date, no longitudinal studies have tested the first part of this developmental model, but two studies have tested the second part. The limited longitudinal evidence suggests that morphological awareness is linked to further development in vocabulary knowledge. McBride-Chang et al. (2005a) found that morphological awareness was related to vocabulary development in a sample of kindergarten and grade 2 children who were native speakers of the Cantonese language (Chinese). Most interestingly, McBride-Chang et al. (2005b) found that morphological awareness explained 10% of unique variance in expressive vocabulary after controlling for phonological processing and reading in a sample of

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kindergarten and grade 2 English-speaking children. These findings are consistent with the view that morphological awareness is a reliable contributor to individual differences in vocabulary knowledge. It would also be of interest to examine whether there is an indirect role for morphological awareness in literacy whereby children with stronger morphological awareness are more likely to employ morphological analysis and, consequently, have a stronger vocabulary, which, in turn, facilitates reading comprehension. Such a model could be tested in future research. We now turn to the relation between morphological awareness and phoneme awareness. D. MORPHOLOGICAL AWARENESS AND PHONOLOGICAL AWARENESS For children just learning to read, the development of phonological and morphological awareness may be reciprocal (Carlisle, 1995; Casalis & LouisAlexandre, 2000). Children with stronger phonological awareness may notice more easily the rhyme of words that end with the same suffix, such as player, farmer, dancer, and baker. Such awareness may be a precursor to acquiring the morphological knowledge that the agentive suffix -er changes a verb into a noun, and, once the morphological knowledge is acquired, it may result in such neologism as storyer. At the same time, the use of inflectional morphology in spoken language may help children learn to manipulate specific phonemic units such as the /s/ in the case of the plural mark. To assess the magnitude of the relation between morphological awareness and phonological awareness, we examined the seventeen studies in Table I that included measures of phonological awareness. These studies represented 2,228 children. The mean correlation between morphological and phonological awareness was moderate (r ⫽ 0.37, CIs ⫽ 0.32 to 0.41, z ⫽ 17.92, p ⬎ 0.001) and the homogeneity statistic was not significantly different from 0, indicating a certain stability across studies (Q ⫽ 18.84, p ⬎ 0.05). These findings are consistent with the notion of a bidirectional relation between phonological awareness and morpheme awareness in which children’s ability to manipulate and segment syllables and rhymes may facilitate the decomposition of words along morphologic boundaries. In return, understanding the morphological relations between words may assist children in their appreciation of the phonemic structure of language. E. INTERVENTION STUDIES Intervention studies have been designed to assess the causal role of morphological awareness in children’s reading and spelling (Arnbak & Elbro, 2000; Lyster, 2002; Nunes, Bryant & Olsson, 2003; Robinson & Hesse, 1981). The findings

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from these studies show that children trained in morphological awareness outperform children in control groups, but that they typically do not outperform children trained in phonological awareness on general measures of reading or spelling. There is some evidence of specific effects, however. For instance, children in Nunes et al. received explicit instruction in word stems and inflectional affixes (past verb endings) and derivational affixes (agentive endings like the -ian in magician). In this study, morphologically trained children spelled past tense suffixes more accurately than did the phonologically trained children. A possible explanation for the lack of strong effects favoring morphology over phonology is offered by Fowler and Liberman (1995), whereby training that aims to foster growth in morphological awareness may have limited success if a child’s phonological skills are weak. It would be interesting to examine whether training phonological awareness first, followed by training morphological awareness, would have greater success in enhancing children’s spelling.

VII. Summary and Concluding Remarks The accumulated evidence that we reviewed suggests that children make use of regularities in the language—be it phonological, orthographic, and morphological— to read and spell words (Christianson et al., 2005). Given that languages vary in the clarity with which oral language is represented in writing, one should expect the relative roles of phonological, orthographic, and morphological processing to vary accordingly. In this chapter, we focused on the relative contribution of morphological analysis and awareness to reading and spelling. We found that the morphological information in complex words can facilitate reading and spelling and that knowledge about the morphemic structure of a language can assist a child in reading, spelling, and deriving the meaning of multimorphemic words. The accumulated evidence also demonstrates that morphological awareness contributes to individual differences in reading and spelling that cannot be entirely subsumed to orthographic and phonological processing. Intervention studies on morphological knowledge (i.e., analysis and awareness), however, have not yielded the strong effects that one would have expected. We suspect that more successful intervention studies on how morphological knowledge can enhance literacy warrant a more thorough understanding of the complex interplay between morphological knowledge and a number of different variables such as oral vocabulary, phonological and orthographic awareness, and reading exposure. Given the demonstrated facilitative effects that morphological information can have on reading and spelling along with the particular difficulties that multimorphemic words can pose, researchers argue that systematic and sequential instruction of morphology is needed during the elementary years of schooling (e.g., Carlisle & Fleming, 2003; Green et al., 2003; Henry, 1993; Worthy & Viise, 1996).

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Morphological rules, however, are currently not taught or taught partially to elementary school children (Nunes et al., 1997a, 1997b). Perhaps, as Carlisle (2003) suggests, this is partly due to the fact that educators are more familiar with concepts of phonemes and phoneme awareness than with concepts of morphemes and morphemic awareness. This may change in time as we cumulate stronger scientific evidence on the valuable role of morphological knowledge in reading and spelling.

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THE INTERACTIVE DEVELOPMENT OF SOCIAL SMILING

Daniel Messinger a and Alan Fogel b a

DEPARTMENT OF PSYCHOLOGY, UNIVERSITY OF MIAMI, CORAL GABLES, FL 33124, USA DEPARTMENT OF PSYCHOLOGY, UNIVERSITY OF UTAH, SALT LAKE CITY, UT 84112, USA

b

I.

II.

OVERVIEW A. THEORETICAL ORIENTATION B. THE NEUROPHYSIOLOGY OF SMILING C. TEMPERAMENT-BASED STUDIES OF SIGHTED INFANTS AND SMILING IN BLIND INFANTS EARLY SMILING A. NEONATAL SMILING B. THE EMERGENCE OF SOCIAL SMILING C. THE EARLY DEVELOPMENT OF SOCIAL SMILING

III.

QUANTITY AND QUALITY A. DIFFERENT TYPES OF SMILING: DIFFERENT TYPES OF POSITIVE EMOTION? B. SMILES AS INDICES OF CONTINUOUS POSITIVE EMOTIONAL PROCESSES C. SMILES AS CONTINUOUS INDICES AND SMILES AS DISTINCT TYPES—A RAPPROCHEMENT?

IV.

THE INTERACTIVE DEVELOPMENT OF SMILING A. OVERVIEW OF INTERACTIVE SMILING B. THE DEVELOPMENT OF SOCIAL SMILING IN INTERACTIVE CONTEXT C. SMILING INTERACTION DYNAMICS D. INFANTS’ PERCEPTIONS OF INTERACTIVE SMILING

V.

VI.

SMILING AND ATTENTION TO THE CAREGIVER A. SMILES AND AROUSAL MODULATION B. THE EARLY COORDINATION OF SMILING AND GAZING AT THE CAREGIVER’S FACE C. THEORETICAL PERSPECTIVES RELEVANT TO SMILES AND GAZE AVERSION SMILING AND REFERENTIAL COMMUNICATION

VII.

PRAGMATICS: THE REPRESENTATIVENESS, DISCRIMINANT, AND PREDICTIVE VALIDITY OF INFANT SMILING A. REPRESENTATIVENESS OF SMILING B. SMILING IN ATYPICALLY DEVELOPING INFANTS C. SMILING AND DEVELOPMENTAL OUTCOMES

VIII.

SUMMARY AND CONCLUSIONS

ACKNOWLEDGMENTS REFERENCES

327 Advances in Child Development and Behavior R.V. Kail : Editor

Copyright © 2007 Elsevier Inc. All rights reserved.

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Infant smiles elicit feelings of sympathetic engagement from researchers as well as parents. Early social smiles appear to be direct behavioral expressions of positive emotional engagement. This apparent link between behavior and meaning lies behind a century of research on the causes, emotional significance, behavioral correlates, and developmental consequences of infant smiles. In this chapter, we review that literature with a critical eye, focusing on the emergence and early development of social smiling, the possibility that different types of smiles index different types of positive emotion and new evidence that smiles index a single dimension of positive emotion, the interactive development of different types of smiling and the origins of emotion regulation, the integration of smiling into referential communication, and the use of smiles to distinguish between infants and predict outcomes. The review covers the results of studies of infant perception, infant smile production, observers’ ratings of those smiles, and the smiling of nonhuman primates. We begin with a theoretical overview, review the neurophysiology of smiling, and examine the heritability of smiling and lessons from the smiling of blind infants. Throughout, our intent is to present new findings and highlight areas of potential investigation.

I. Overview A. THEORETICAL ORIENTATION More than a century of research into emotional expression has produced a rich diversity of theoretical perspectives. Here we provide a brief overview of those perspectives as they pertain to the development of smiling. No attempt has been made to explicate each perspective or its variants fully. Instead our goal is to identify the strengths of these perspectives and situate our own approach with respect to them. This will involve noting areas of overlap—as well as divergence— between theoretical perspectives on the development of smiling. Cognitive/constructivist (differentiation) approaches suggest that discrete affects develop from earlier more diffuse states. Joy, for example, develops out of states of pleasurable positive valence (Sroufe, 1979, 1995; Sroufe & Waters, 1976). This perspective is part of a long theoretical tradition suggesting that emotions occur only in the presence of a cognitive interpretation of affective valence (Barrett, 2006; Bridges, 1932; Sroufe, 1995). Smiles in the first 2–3 months are thought to index pleasure and to occur when the infant experiences a relaxation in cognitive tension related to recognizing a visual stimulus. The development of an increasing capacity for cognitive engagement is thought to lead to more dramatic drops in arousal and more specifically joyful emotion (Sroufe, 1995; Tomkins, 1962). These developments are thought to occur around 9 months and to be paralleled by more intense infant smiling and laughing (Sroufe, 1995).

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Differential and discrete emotion theories champion the straightforward hypothesis that infant facial expressions such as smiles are the product of discrete affect programs (Ackerman, Abe, & Izard, 1998; Izard & Ackerman, 2000; Lewis, 2000). These neurophysiologically based affect programs simultaneously trigger expressive actions such as smiles and feeling states such as joy. By positing that infant smiles are direct indices of joy, this perspective has facilitated extensive research in which smiles are measured among different infant populations at different ages. This theory focuses on structures within the organism that are responsible for emotion and its expression. Recent articulations of differential emotion theory, however, have stressed a functional role for emotions. Joy, for example, is thought to motivate social approach behaviors and the continuation of interactions. At a societal level, smiles are seen as communicating positive feelings and facilitating social cohesion. An early propensity toward joy, as expressed in smiling, is hypothesized to facilitate extraverted personality traits. Functional perspectives focus on the role of emotions such as joy in the creation and maintenance of relationships with the environment, particularly with significant others (Barrett, 1993; Campos et al., 1994; Witherington, Campos, & Hertenstein, 2001). This perspective has served to direct attention to vocal, gestural, and wholebody expressions of emotion in context, warning against exclusive reliance on smiles or other facial expressions of emotion. Potentially relevant to functionalist perspectives are ethological attempts to understand smiles solely as communicative signals to conspecifics (Fridlund, 1994). Ethological approaches have generated impressively clear research results on the communicative functions of smiles and similar expressions in monkeys, chimpanzees, and human beings (Bard et al., 1992; Burrows et al., 2006; Mizuno, Takeshita, & Matsuzawa, 2006; Redican, 1975; van Hooff, 1972). Functionalist approaches stress the importance of identifying the infant’s goal orientation in a given situation and suggest, along with other approaches, that joy is a product of goal attainment. Our approach uses dynamic systems as a higher order theoretical orientation with which to integrate insights from other perspectives (Camras, 2000; Fogel et al., 1992; Messinger, Fogel, & Dickson, 1997; Thelen & Smith, 1994; Thelen & Ulrich, 1991; Witherington et al., 2001). A dynamic systems approach focuses on social smiling as a reflection and constituent of an interactive relationship. The focus is the bottom–up interrelationship of constituents of positive emotional expression as they emerge in social contexts. This approach has also focused on the temporal dynamics of social smiling, their rise and fall in time, and the relation of such emergent processes to emotional development more generally. This has involved examining the creation of smiles and other facial expressions in real time and the possible ramifications of such real-time processes for emotional development. From a dynamic systems perspective, expressive configurations such as smiles are conceptualized as constituents of infant emotional processes. The expression

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is part of what the infant feels and is central to the infant’s ongoing interchange with the environment. Smiles are an emotional signal to the self as well as the interactive partner. They are simultaneously experiential and social. As such, the dynamics of facial expression can shed light on the dynamics of emotion. By using a dynamic systems approach as a higher order theoretical framework, we seek in part to emphasize areas of overlap and agreement between different perspectives. Differing theoretical perspectives define emotion in different ways and emphasize different research agenda, creating overlaps between perspectives. Both functional and dynamic systems approaches, for example, locate emotion in the relationship of the infant to his or her environment. A cognitive/constructivist perspective highlights developing cognitive capacities in the emergence of smiling in a fashion that exemplifies the dynamic systems emphasis on nonobvious components in the bottom–up emergence of emotional expressions. Though only differential emotion theory may emphasize the logical primacy of the neural components of positive emotional functioning, no perspective challenges their importance. Finally, both differential emotion theories and dynamic systems approaches are concerned with the temporal dynamics of smiles—albeit for different reasons.

B. THE NEUROPHYSIOLOGY OF SMILING The neural origins of smiling are clear (Elliot, 1969; Williams et al., 1989). Smiles occur when the zygomatic major muscle contracts, pulling the corners of the lips upward and laterally (see Figure 1). The zygomatic is innervated by the facial nerve, the seventh cranial nerve, which emanates from the facial nucleus. The facial nucleus is an aggregation of motor neurons in the ventrolateral region of the lower pontine tegmentum, at the level of the pons in the brain stem. By contrast, afferent sensation from the face during smiling is carried by the fifth cranial nerve, the trigeminal. This afferent feedback may be a physiological basis for the facial-feedback hypothesis. Empirical support for this hypothesis indicates that the process of smiling can itself contribute to the experience of joy (Izard, 1981; Soussignan, 2002). The neurophysiological evidence of an affect program for joy is less than clear. The facial nucleus receives two sets of inputs. Voluntary or deliberate smiling (being asked to produce a smile) is thought to originate in the cortical motor strip and travels to the nucleus via pyramidal tracts (Rinn, 1984). However, most social smiling in infancy is spontaneous and expressive and, according to differential emotion theory, is a motor expression of an affective neural program for joy. Spontaneous facial expressions involve an “extrapyramidal” pathway that involves subcortical (e.g., basal ganglia) as well as deep cortical structures such as the amygdala.

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Fig. 1. Six-month-old infant displaying a high-amplitude interactive smile involving eye constriction and mouth opening.

Reviews of neuroimaging studies in adults (Barrett & Wager, 2006) suggest that joyful responses may not be associated with a specific pattern of activation (Murphy, Nimmo-Smith, & Lawrence, 2003; Phan, Wager, Taylor, & Liberzon, 2004). One meta-analysis reviewed suggests an association between joy and activation of the rostral supracallosal anterior cingulate cortex (Murphy, NimmoSmith, & Lawrence, in press). Another suggests an association between joy and activation of the basal ganglia, a set of structures associated with voluntary movement (Phan et al., 2004). One possibility is that anterior cingulate cortex, a section of limbic cortex, is associated with joyful responses, whereas basal ganglia are involved in related action tendencies. Nevertheless, the lack of consistency does not readily suggest support for an affect program as there is no consistent neural pathway for joy. Stronger meta-analytic evidence (Barrett & Wager, 2006) supports the supposition that positive affect and approach-oriented emotional orientations are associated with greater left than right cerebral activation both overall (Murphy et al., 2003) and specifically in frontal areas (Wager et al., 2003). This pattern of activation also accompanies emotionally positive Duchenne smiles, which involve constriction of the eyes, in infants (Fox & Davidson, 1988). These left frontal areas, however, are not dedicated structures. Instead, specific elements of perceiving and acting joyfully in an interactive situation (e.g., smiling while gazing at and moving toward a parent) may yield more consistent patterns of neurophysiological activation than investigations of abstracted emotion categories such as joy (Barrett & Wager, 2006). As suggested by a dynamic systems approach, the neural “structure” of joyful smiling is likely to be both embodied and interactive (Fogel & Thelen, 1987).

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C. TEMPERAMENT-BASED STUDIES OF SIGHTED INFANTS AND SMILING IN BLIND INFANTS In this section, we examine temperamental approaches to the smiling of sighted infants, which provide an overview of factors impacting the expression of positive emotion. These temperamental approaches are complemented by reports on smiling in blind infants, which illustrate how smiling develops in the absence of visual input. There tends to be a gap between broad-scope temperamental approaches to infant positive emotion expression and more detailed interactive approaches. Investigations of temperament often employ genetically informative designs and employ linear modeling of heritable and environmental variance of indices of positive emotion. Interactive approaches investigate the development and intime formation of positive emotional communication. The approaches are ultimately, however, complementary views of similar phenomena at different levels of analysis. Patterns of parental response reveal the influence of both genetic and environmental effects on infant positive emotion expression (Goldsmith, Buss, & Lemery, 1997; Goldsmith et al., 1999). This is in contrast to reports on negative emotion in which heritability estimates tend to be higher and environmental influences less pronounced. Shared environmental effects on infant expression of positive emotions include caregiving effects such as the impact of parent–child interaction. Genetically informative temperament studies are typically based on parental reports of positive emotion (Goldsmith et al., 1997, 1999). Parents’ reports of infant smiling and laughter sometimes are and sometimes are not significantly correlated with investigator observations of positive emotion expressions (Bridges et al., 1993; Rothbart, 1986). One possibility is that parental ratings are relatively uninformative when the parents engage in high levels of emotionally positive play with their infants (Hane et al., 2006). It is only the ratings of parents who engage in low levels of mutually positive play with their infants that are predictive of observed infant smiling. Clearly, genetically informative studies of investigator-observed expressions are necessary to shed light on the relative impact of heritable and environmental factors on infant social smiling. The development of smiling in blind infants provides intriguing clues into the role of environmental influences in the emergence of positive facial expressions (Fraiberg, 1975; Freedman, 1964; Ganchrow, Steiner, & Daher, 1983; Rogers & Puchalski, 1986; Thompson, 1941). Social smiling in blind infants occurs in response to events such as hearing a familiar voice. It typically elicits a parental response. Perhaps as a consequence, these social smiles become more frequent between 4 and 12 months. However, the smiles of blind infants are less frequent and briefer (more fleeting) than those of sighted infants. Deficits in smiling are

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observed in blind infants after 2 or 3 years of age. On the one hand, normative experiences of caregiving are sufficient for the emergence of smiling; on the other hand, visually mediated interactive smiling appears to play an important role in maintaining smiles in real time (i.e., the duration of smiles) and in developmental time (i.e., the reduced smiling of older blind infants). Research with blind infants suggests that the emergence of social smiling is experience expectant, occurring even in the absence of visual feedback. The interactive intensification of smiling depends, however, on visual engagement. From a dynamic systems perspective, the absence of mutually reinforcing visually mediated feedback in the form of reciprocal smiling probably plays a role in these deficits. In the next section, we broaden our scope to examine the early development of smiling in typically developing infants.

II. Early Smiling A. NEONATAL SMILING In early development, neonatal smiling gradually becomes linked to environmental stimulation, setting the stage for the emergence of social smiling. In this section, we describe the association of neonatal smiles with particular behavioral states, their cortical origins, and observer studies of neonatal smiles. We go on to describe the anatomical topography of neonatal smiles and the subsequent development of smiling in response to sensory stimuli that set the stage for social smiling. Neonatal smiles appear to be experience expectant. They occur in sleeping and drowsy states of rapid eye movement (REM) at an average rate of one smile per 5 min. Smiles during sleep are referred to as spontaneous or endogenous smiles because they have no obvious external cause (Emde et al., 1978; Emde & Koenig, 1969a, 1969b; Emde, McCartney, & Harmon, 1971; Harmon & Emde, 1972a, 1972b; Messinger et al., 2002; Wolff, 1987). Newborns also smile, though less frequently, during other behavioral states, including states of alertness (Dondi et al., 2006). A case report of neonatal smiling in an infant with microcephaly suggests a subcortical origin for neonatal smiling (Emde & Koenig, 1969a, 1969b; Emde et al., 1971; Harmon & Emde, 1972a). Developing cortical inhibition of smiling is suggested by the findings that infants born prematurely show more neonatal smiling than full-term infants and that this spontaneous smiling declines with age. Neonatal smiles illustrate the dynamic principle of developmental heterochronicity (Fogel & Thelen, 1987). Smiles are present physically before they are integrated into patterns of social engagement and interaction that provide

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evidence for joyful emotion. Neonatal smiles can, in fact, have a relatively mature form in which the zygomatic shows moderately strong contraction and the eyes are constricted to form a Duchenne smile (Messinger et al., 2002). This association between the strength of smiling and the strength of eye constriction reflects an early, apparently neuromuscular, synergy. In humans, zygomatic contractions during sleep appear to decline in frequency as stronger zygomatic contractions during alert states become more frequent toward 1 month of age (Harmon & Emde, 1972a; Wolff, 1987). This pattern in human infants has similarities with accounts of smiling in young chimpanzees (Mizuno et al., 2006). Chimpanzees also smile during REM sleep; this smiling declines in the first 2 months of life as social smiling increases. Although smiles can have an apparently mature form at birth, these patterns of increasingly strong and bilateral zygomatic contraction suggest a developmental process of neuromuscular coordination and synchronization that is consistent with a dynamic systems perspective. Influenced by a dynamic systems perspective, Wolff (1987) documented the developmental emergence of infant smiling in response to first auditory and then visual stimuli in the first 2 months of life (Field et al., 1986; Spitz, 1946; Sroufe & Waters, 1976). In the first week of life, infants do not smile reliably in response to sounds, visual stimuli, tactile stimulation, bouncing, or the like. Toward the end of the second week, half of the infants in Wolff’s sample smiled regularly in response to the human voice when they were awake. By the fourth week, most infants smiled to both human and nonhuman sounds, although the human voice was more attractive. At 5 weeks, the combination of voice and face was a better elicitor of smiling than either of the two alone. By 8 weeks, infants smiled only after making visual contact with the mother’s face (Harmon & Emde, 1972a; Spitz, 1946; Wolff, 1987). An explanation of the apparent shift in the capacity of first auditory and then visual stimuli to elicit smiling might invoke features of the developing nervous system first in a uterine and then in an extrauterine environment (Huttenlocher, 1999; Lickliter & Bahrick, 2001). New descriptive and experimental studies such as those pioneered by Wolff are warranted. They would indicate whether individual differences in central nervous system maturity and/or early experience with smile-eliciting stimuli are related to the development of smiling responses to mechanical stimuli and indicate whether such smiling responses are linked to the emergence of social smiling (Kawakami et al., 2006). B. THE EMERGENCE OF SOCIAL SMILING Smiles develop their familiar social form during interaction. Although mothers report the emergence of social smiles at about 1 month, experimenters are able to elicit social smiles between 1 and 2 months (Anisfeld, 1982). The emergence

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of social smiling, however, appears to be contingent on postconceptional age in both preterm and full-term infants. This suggests social smiling is a function of neurological maturity rather than number of weeks in the postnatal environment, a possibility that appears ripe for further empirical study. Social smiling develops as infants spend more time in states of alert inactivity (i.e., not fussing/crying) that facilitate gazing at the caregiver’s face (Lavelli & Fogel, 2005). Social smiles, in fact, emerge in a period marked by the development of new patterns of visual attention. Although 1-month-olds gaze alternately at the edge of the head and the eyes, 2-month-olds gaze between the edge of the head, the eyes, and the mouth. This more integrative pattern of gazing is likely to encourage attention to the facial expression of others. Thus, linked components of neural maturity, state regulation, and perceptual competence appear to be necessary for the emergence of social smiling. Social smiles are not present at birth. From an evolutionary perspective, the function of smiles is to keep parents and other potential caregivers close at hand (Bowlby, 1982). It is not clear, however, that observational studies have systematically examined whether infant smiles, in fact, predict increased parental proximity. Nevertheless, it appears plausible that earlier social smiling would increase an infant’s inclusive fitness. It may be, of course, that heritable changes associated with the earlier emergence of social smiling are not available during the first month of postnatal physiological consolidation and energy conservation (Rovee-Collier, 1996; Sroufe & Waters, 1976). There is, however, some evidence suggestive of potentially heritable differences in the development of social smiling. Group differences have been documented in the emergence of social smiling in an Israeli sample (Anisfeld, 1982). Both tester and maternal observation indicate that Sephardi Jewish infants engaged in social smiling about 1 month before Ashkenazi Jewish infants. Such a difference suggests a background of potentially heritable individual variability in the timing of the onset of social smiling. If such differences are, indeed, heritable, age of social smiling may be subject to evolutionary pressure. A crucial issue here is the psychological meaning of the emergence of social smiling to parents. A testable hypothesis with clear evolutionary implications holds that the emergence of social smiles would be associated with parental reports of increases in a feeling of connection or even a willingness to sacrifice for the newly smiling infant. C. THE EARLY DEVELOPMENT OF SOCIAL SMILING In this section we outline the developmental emergence of social smiling in a dyadic context. Inspired by Trevarthen’s microanalytic observations (Murray & Trevarthen, 1986; Trevarthen, 2001), we examine how early smiling emerges

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a. Neutral/Simple Attention. Reflexes and vegetative movements. Relaxed neutral expression, possible visual attention, quiet alert. (a) c. Excited Attention. Brow raising (AU 1+2) & strong fast limb movements. Mouth closed or only partially open. High-arousal & sustained visual attention with motor excitement.

(b)

d. Astonished Attention. Strong brow raising (AU 1+2); motor quiet, relative facial stillness. Eye widening (AU 5); jaw dropping and mouth open in “o”-shape. “Fascinated,” motionless visual fixation.

e. Attentive Smile. Lip (c) corner raising (AU 12) with mouth only partially open. Frequent motor quiet. Relaxed expression of pleasure during visual attention.

(d)

f. Cooing Expression. Lip shaping for cooing, with upper lip raising / protrusion, or lip & tongue “pre-speech” movements. Approaching postural orientation; arm raising with arm / hand waving.

(e)

(f)

Fig. 2. Infant expressive configurations during mother–infant face-to-face communication (0–3 months). Source: Lavelli and Fogel (2005).

from attentional expressive configurations (Lavelli & Fogel, 2002) (see Figure 2). We employ a dynamic systems perspective to find parallels between the realtime and the developmental emergence of positive facial expressions during social exchanges in the first 3 months of life. In the first month, infants transition between neutral gazes away from mother’s face and simple attention to her face (i.e., gazing at the mother’s face without any sign of emotional engagement). The second month sees a sequential pattern of infant simple attention to mother’s face, concentrated attention to her face, smiling at mother, and then cooing expressions also directed toward mother. This pattern is an interactive replication of findings that dynamically link cognitive processes to the emergence of social smiling as predicted by both cognitive/constructivist and dynamic systems approaches. Early social smiling is frequently preceded by a 3- to 20-s period of brow knitting and visual fixation on the mother’s face (Anisfeld, 1982; Lavelli & Fogel, 2005; Oster, 1978). The brows then relax, indexing apparent cognitive recognition, and a smile appears. Real-time occurrences of this attention-related smiling pattern may, then, be the occasion for the developmental emergence of smiling. Research further specifying the type of cognitive processing preceding the occurrence and developmental emergence of social and nonsocial smiles would strengthen this conclusion. During the second month maternal expressions change in a manner that parallel developmental changes in the infant’s patterns of attention and emotion during

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face-to-face communication (Lavelli & Fogel, 2002). Maternal neutral expressions decrease in conjunction with an increase in approach-oriented emotionally positive expressions in which mothers talk and smile simultaneously (talk/smile). At a dyadic level, infant smiling and cooing expressions become sequentially linked with maternal talk/smile in the second and third month. These sequential linkages are bidirectional. Maternal talk/smile, infant smile, and infant cooing expressions can cycle between each other in multiple patterns, suggesting the existence of a positive emotional attractor in the social communication system. Taken together, these findings suggest that the smile does not occur alone but rather develops in a complex relation with other facial expressions, infant attention, and maternal facial expressions and attention. There is, in other words, a dynamic social–communicative system in which smiling develops and stabilizes. This suggests that smiling gradually develops as infants and their caregivers cocreate specific forms of social communication. In support of this proposition, 2-month-olds smile less at a stranger who is either more or less contingently responsive than the infant’s mother (Bigelow & Rochat, 2006). That is, dyadspecific levels of interactive contingency that affect smiling levels develop by 2 months of age.

III. Quantity and Quality Some smiles appear to be coy, others gleeful, and yet others riotous. In this section, we explore evidence suggesting that different types of smiling express qualitatively different types of positive emotion. This issue is theoretically meaningful. A multiplicity of emotionally different smiles would challenge the discrete emotion theory proposition of a single affect program for joy. In the next section, we present evidence for an alternate possibility—that social smiles express different degrees of a single dimension of positive emotion or joy—and attempt to integrate those perspectives. We begin this section by exploring the possibility that the presence of the Duchenne marker (eye constriction) and of mouth opening may index qualitatively different dimensions of emotional meaning in smiles. A. DIFFERENT TYPES OF SMILING: DIFFERENT TYPES OF POSITIVE EMOTION?

1. Smiles Involving Eye Constriction—Duchenne Smiles Researchers have long argued that Duchenne smiles (Duchenne, 1990 [1862]) involving eye constriction (produced by the orbicularis oculi and pars lateralis) are qualitatively different from smiles without eye constriction (see Figure 3).

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5.0

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Eye Constriction (Duchenne)

Mouth Opening (Play)

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Fig. 3. Smile types.

One hypothesis is that (adult) smiles involving eye constriction are an expression of joy, but smiles without eye constriction are a nonemotional social signal (Ekman, Davidson, & Friesen, 1990). A similar distinction has been made for infants (Dawson et al., 1997; Fox & Davidson, 1988). Ten-month-olds are more likely to produce smiles involving eye constriction when approached by their smiling mothers but are more likely to produce smiles without eye constriction when approached by an impassive stranger. Concurrent electroencephalogram (EEG) recordings indicate that 10-month-olds’ smiling with eye constriction is associated with greater relative activation of the left than the right frontal cerebral hemisphere (Fox & Davidson, 1988). Similar differences in relative activation are found in adults and appear to reflect greater approach orientation (Ekman et al., 1990; Murphy et al., 2003). This suggests that by 10 months there are at least two qualitatively different smiles: smiles with eye constriction used to express joyful engagement and smiles without eye constriction indexing a more cautious or less involved engagement. A similar argument can be made for the qualitative distinctiveness of smiles with eye constriction produced by infants during face-to-face interactions with their mothers: Between 1 and 6 months, infants engage in relatively more smiling with

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eye constriction than smiling without eye constriction when their mothers are smiling (Messinger, Fogel, & Dickson, 2001). During these smiles with eye constriction, they produce more speech-like syllabic sounds than during smiling without eye constriction, suggesting greater engagement with their partners (Hsu, Fogel, & Messinger, 2001). The results suggest smiling with eye constriction is a way to engage with the joyful expressions of another, a way to share positive affect during an ongoing interaction. One hypothesis is that infant smiles involving eye constriction are used to reciprocate the smiles of a social partner and, perhaps especially, to reciprocate the eye constriction smiling of another (Bachorowski, 1999). The presence of eye constriction in an expression may, then, index qualitatively different emotional processes than are present in expressions without eye constriction. Eye constriction, for example, appears to index qualitative change in its occurrence with cry-faces, the prototypic infant negative expressions. Standard descriptions indicate that intense eye constriction transforms the cry-face from a discrete expression of anger into one of distress (Bolzani-Dinehart et al., 2005; Izard, Dougherty, & Hembree, 1983; Messinger, 2002; Oster, Hegley, & Nagel, 1992). One hypothesis is that as eye constriction reduces the visual field it may contribute to a focus on the object of the emotion and to feelings of being caught up by the emotion (Messinger, 1994). Infant smiles with eye constriction may involve increased salience of positive feeling and also communicate this to the receiver. As such, smiles with eye constriction may be perceived to be more authentic infant expressions of joy than smiles without. 2. Smiles Involving Mouth Opening—Play Smiles Another facial action that may produce qualitative changes in the meaning of infant smiles is mouth opening produced by jaw dropping. Mouth opening is associated with more rapid breathing, with vocalizations, and with laughter. Just as eye constriction may index positive emotional engagement with another, mouth opening may index aroused excitement and playfulness. Other evidence concerning the function of open-mouth smiling comes from studies of primates (Bard et al., 1992; Burrows et al., 2006; Plooij, 1979; Redican, 1975). Chimpanzee zygomatic contraction produces a display of silent bared teeth, which seems to be a signal of submission (“I mean you no harm”) that is frequently issued to a dominant individual. In chimpanzees, it has also come to be a signal of affiliation that is followed by behaviors such as holding out a hand. Among human beings and their predecessors, the silent bared teeth display may have evolved into smiling that does not involve pronounced mouth opening. By contrast, the relaxed open-mouth display—also called a play face—is thought to be evolutionarily linked to human laughter and has morphological similarities with open-mouth smiling (Plooij, 1979; van Hooff, 1972; Waller & Dunbar, 2005). Both communicate a playful orientation that has an aroused quality. The chimpanzee relaxed open-mouth display, although common in affiliative contexts, is uniquely

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linked to play. When two chimpanzees both engage in relaxed open-mouth displays, play bouts tend to last longer (Waller & Dunbar, 2005). In chimpanzee infants, it originates in mock biting play with the mothers (Plooij, 1979). One possibility is that, in human infants as well, open-mouth smiles reflect and communicate states of excited arousal and are a prototypic expression of social joy. Like chimpanzees, human infants also engage in mouth opening that is not associated with smiling or with negative expressions, such as the “cooing expression” shown in Figure 2 (Kaye & Fogel, 1980; Messinger et al., 2001). These mouthopen displays tend to occur during positive periods of face-to-face interaction such as when the mother is smiling and making exaggerated displays and when the infant is gazing at the mother. Intriguingly, this suggests that mouth opening, like smiling, may be a characteristic of a relatively positive infant emotional engagement with the environment. Relaxed open-mouth displays may also be phylogenetic precursors of human laughter. In infants, laughter is a smile-linked vocalization that appears to index intense positive emotion. Social routines (including tickling) and visual surprises (covering and uncovering objects) become more potent elicitors of laughter in the first year of life (Nwokah et al., 1999, 1994; Sroufe & Waters, 1976; Sroufe & Wunsch, 1972). After 4 months of age infants laugh more frequently and the mean duration of these laughs increases. At the same time, the duration of the laughs of individual infants and mothers becomes more correlated. In the second year of life, the onsets and offsets of infant and mother laughs that overlap move increasingly closer in time. Both of these developments suggest the development of dyad-specific patterns of positive communication (Nwokah et al., 1994). Such correspondences between partners are suggested by a dynamic systems perspective and are likely to characterize dyadic patterns of smiling. as well as laughing. Nonhuman relaxed open-mouth displays also have special ties to human openmouth smiling. During face-to-face interaction, infants between 1 and 6 months of age engage in more open-mouth smiling when gazing at their mothers’ faces. Among adults, open-mouth smiles involving eye constriction tend to occur in response to humorous stimuli (Ruch, 1997). Although neonates in sleeping and drowsy states emit smiles with eye constriction, smiles with mouth opening are much less frequent, offering indirect support for the arousal hypothesis (Messinger et al., 2002). This pattern of results suggests an association between positive social engagement, arousal, and smiles involving mouth opening. In support of this association, still images of smiles with greater mouth opening are rated as involving more arousal than digitally edited versions of the same smiles involving less mouth opening (Bolzani-Dinehart et al., 2003, 2005). The association between mouth opening and arousal is also seen in ratings of the negative, cry-face expression (Bolzani-Dinehart et al., 2005). We have suggested that expressions involving eye constriction index the increased salience of the emotional experience and that expressions involving mouth

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Fig. 4. An illustrative circumplex showing emotional valence on the horizontal axis and arousal on the vertical axis. Sad and angry faces indicate negative emotional valence, while smile-faces indicate positive emotional valence. Greater mouth opening indicates greater arousal regardless of emotional valence. At the highest level of arousal, the distinction between positive and negative emotional valence is lost. At the lowest level of arousal, no emotional valence is conveyed. Figure and caption courtesy of Mark Sheskin.

opening index increased arousal. These qualitative distinctions between facial expressions can be mapped onto circumplex models of emotion (Barrett & Russell, 1999; Russell, 1980; Yik, Russell, & Barrett, 1999) (see Figure 4). In this model, positive (pleasant) and negative (unpleasant) affect define two horizontal poles.

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We hypothesize that such positive (smile) and negative (cry-face) expressions involve eye constriction. These expressions may communicate that the infant is in the throes of a “deeper” emotional experience. This valence dimension is at right angles to an arousal dimension. Emotion expressions high in arousal are hypothesized to involve mouth opening. Among infants, this would involve smiles with mouth opening in the upper right quadrant and cry-faces with mouth opening in the upper left quadrant. At the top of this pole, arousal becomes so extreme as to dominate the valence. In the same way, expressions of extreme arousal are hypothesized to involve extreme mouth opening that stretches out facial features, erasing the distinctive positive and negative characteristics of the expression. 3. Smiles Involving Both Eye Constriction and Mouth Opening—(Duplay Smiles) Based on the meaning of their facial constituents, infant smiles that combine eye constriction and mouth opening (duplay smiles) are hypothesized to index sharing experiences of aroused positive engagement. During face-to-face interactions, these smiles are relatively more likely when infants are gazing at their smiling mothers (Messinger et al., 2001). Levels of this type of smiling also vary systematically over the episodes of the face-to-face/still-face procedure (Adamson & Frick, 2003; Delgado, Messinger, & Yale, 2002; Moore, Cohn, & Campbell, 2001; Tronick et al., 1978). Levels of combined open-mouth smiling with eye constriction are relatively elevated during the initial face-to-face interaction. They are relatively depressed during the stress of parental nonresponsivity in the still-face and the emotional regrouping that characterizes the reunion episode (Weinberg & Tronick, 1994). The meaning of different types of infant smiles is revealed in peekaboo and tickle games between mothers and infants (Fogel et al., 2006). Both games involve a setup phase and a more intensely emotional climax phase. In peekaboo, the setup is the covering of the mother’s face (“Where’s mommy?”), and the climax is the uncovering (“Peekaboo”). Infants were more likely to smile during the climax than during the setup of peekaboo games but this pattern did not vary by type of smile. Different phases of tickle games were associated with different types of smiling. In tickle games, the setup is the approach of the mother’s hands toward the infant’s body (“I’m gonna get you”), and the climax is the act of tickling (which may be accompanied by maternal vocalizations). Among infants at 6 and 12 months of age, combined open-mouth smiles with eye constriction tended to occur during the climax rather than during the setup phase of tickle games. This parallels the finding that, at home, 12-month-olds’ combined openmouth smiling with eye constriction predominates during physical play with parents (Dickson, Walker, & Fogel, 1997). These findings offer additional support

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for the view that smiling involving eye constriction and mouth opening indexes sharing experiences of aroused positive engagement. Approach and withdrawal indexed by patterns of gazing and movement during games also contribute to the meaning of smiles (Fogel et al., 2000). During peekaboo games, for example, infants tend to gaze at the parent during all types of smiles, suggesting approach-oriented visual attention. During the climax of tickle games, by contrast, infants engaging in open-mouth smiles with eye constriction show mixed patterns of both gazing at and away from parents. Such patterns may correspond to feelings of enjoyment of active participation in a highly arousing situation and enjoyment of escape. These findings suggest that the same smiling actions can reflect different positive emotions depending upon co-occurring infant actions and the dynamics of the social process. B. SMILES AS INDICES OF CONTINUOUS POSITIVE EMOTIONAL PROCESSES In addition to evidence suggesting the existence of qualitatively different positive emotions indexed by different types of smiles, there is also strong evidence that smiles vary in the degree to which they express a single joyful positive emotion. This argument rests on examination of the strength of the smile action itself (smile amplitude, a continuous measure of the strength of zygomatic contraction), consideration of the role of amplitude in smiles involving eye constriction and mouth opening, the distribution of these types of smiles in different periods of interaction, rating studies, and the results of automated measurements being used to describe smile processes in time. 1. Smiling as a Continuous Action Physiologically, smiles are continuous neuromuscular processes. The strength of zygomatic contraction determines, other things being equal, the amplitude of a smile, the extent of upward and lateral lip corner movement. If zygomatic contraction indexes positive emotion, it follows that stronger contraction indicates more intensely positive emotion. In fact, adults’ self-reported feelings of pleasure are correlated with the amplitude of zygomatic major contraction in studies using both observational (Ekman, Friesen, & Ancoli, 1980) and electromyographic methods (Hess et al., 1989). Similarly, smile amplitude appears to index directly the infant’s positive emotional engagement with ongoing activities. Tickle games elicit higher amplitude smiling than peekaboo games. The climax of both games involves smiles of higher amplitude than the setup phases. Perturbations that involve dampening the climaxes of the games—such as substituting pretend for real tickling—result in lower-amplitude smiles (Fogel et al., 2006).

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2. Smile Amplitude in Different Types of Smiles Coding of the mean amplitude of different types of smiles suggests anatomical constraints (Fogel et al., 2006) and the possibility that different types of smiles index different degrees of positive emotion. Despite evident variability within each type of smile, simple smiles show the lowest mean amplitude followed by open-mouth smiles, smiles with eye constriction, and then smiles that involve both mouth opening and eye constriction (see Figure 3). Both in the presence and in the absence of mouth opening, smiles with eye constriction tend to involve stronger zygomatic contraction. This is likely due to the synergistic functioning of these muscles. The muscles are agonists that raise the cheek and may share common pathways of innervation (Williams et al., 1989). This synergy is also presumably responsible for the tendency of some interactive smiles to “recruit” eye constriction as their amplitude increases (Messinger, Fogel, & Dickson, 1999; Messinger et al., 1997). By contrast, the tendency of smiles involving mouth opening to involve stronger zygomatic contraction than smiles without seems to resist those anatomical constraints. Stronger mouth opening is likely to be somewhat antagonistic to upward lip corner movement. This patterning is consistent with the view that eye constriction and mouth opening index the increased positive emotional intensity of smiling. 3. The Distribution of Smiles Types During Interaction Even absent the dimension of smile amplitude, the occurrence of different types of smiles in different social situations supports the argument that infant smiles index a continuous positive emotion dimension. Simple smiles—those involving neither eye constriction nor mouth opening—are more likely to occur during periods of interaction likely to elicit positive emotion than are nonsmiles. These are periods of time when infants gaze at their mothers and when their mothers smile. By the same token, infant smiles involving eye constriction and mouth opening are relatively more likely than simple smiling in the same social situations. A conclusion is that simple smiles are more emotionally positive than neutral expressions, but smiles involving eye constriction or mouth opening are more emotionally positive than simple smiles. Different types of smiles, then, may reflect a continuous likelihood distribution of occurrence in affectively congruent situations, suggesting support for an underlying continuous dimension of positive emotion. 4. Rating Studies The view that all infant smiles are emotionally positive but some infant smiles are more positive than others (Messinger et al., 2001) is supported by observers’ ratings of still images of smiles. Undergraduates rate simple smiles as more emotionally positive than nonsmiling neutral expressions (Messinger et al., 2001). They rate smiles involving eye constriction and smiles of greater amplitude more

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positively than, respectively, smiles without eye constriction and smiles of lower amplitude (Bolzani-Dinehart et al., 2005). Smiles involving mouth opening also tend to be rated more positively than smiles without mouth opening, but this effect can be more subtle. The association between mouth-open smiles and greater positive emotion sometimes requires a rater who is a parent of an infant or is visible to a nonparent student rater only when video clips (rather than still images) are displayed (Cassel et al., 2004). Indirect support for the emotional intensity hypothesis stems from parallel findings with cry-faces. Student raters perceive cry-faces involving greater eye constriction (all cry-faces involve at least some eye constriction) as more negative than the same cry-faces with minimal eye constriction (Bolzani-Dinehart et al., 2005; Messinger, 2002). They perceive cry-faces involving greater mouth opening as more negative than cry-faces with less mouth opening. This suggests that the features that index stronger positive affect in smiles also index greater negative affect when they occur with some negative expressions. 5. Automated Measurements of Smiles The research we have reviewed suggests that infant smile amplitude, eye constriction, and, perhaps to a lesser extent, mouth opening, are cumulative indices of positive emotional intensity. A premise of this research is the existence of distinct types of smiling. Emerging research techniques, however, are offering portraits of smiling and infant–mother interaction as continuous processes in time (Cohn & Kanade, in press; Cohn & Schmidt, 2004; Cohn et al., 1999; Messinger et al., 2005; Schmidt et al., in press; Schmidt, Cohn, & Tian, 2003). We have complemented software measurements of facial features indexing the intensity of infant and mother smiles (see Figure 5) with nonexpert real-time ratings

Fig. 5. Four-month-old infant and mother smiling interaction captured by Automated Face Analysis at Carnegie Mellon University, Robotics Institute. Analysis compliments of Jeffrey Cohn, Ph.D. Each partner’s face is outlined to illustrate lip movement, mouth opening, and eye constriction, and these outlines are reproduced in iconic form to the right of each partner.

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of the affective valence of the smiles (Messinger et al., 2005). Moment-by-moment analyses using software measurements reveal that, during face-to-face interaction, a single infant or mother smile can ebb and flow in amplitude over periods of 20–30 s (see Figure 3). Such lengthy smiling does not correspond to discrete emotion accounts of smiles as relatively brief, highly constrained (Ekman & Davidson, 1994; Frank, Ekman, & Friesen, 1993). Infant and mother interactive smiles have a continuous structure. In the course of their smiles, both infants and mothers show a high correlation between smile amplitude and eye constriction. That is, when infants and mothers smile more strongly they also show greater eye constriction. It is frequently argued that Duchenne smiles express joy but non-Duchenne smiles are a social signal unrelated to positive emotional expression (Ekman et al., 1990; Frank et al., 1993; Soussignan, 2002). Eye constriction that waxes and wanes within a smile, however, may divide a smile into periods in which it is and is not a smile with eye constriction. It seems unlikely that some of those periods are emotional while others are not. The finding that eye constriction changes continuously in concert with smile amplitude suggests difficulties with the division between Duchenne and nonDuchenne smiles in infancy. Such dichotomies appear to rest on underlying continuous changes in smile intensity. This suggests the need for new units of analysis that transcend smile types. The rise and flow of a single smile in time is one candidate; another potential unit of analysis is a bout of infant smiles that may have brief periods of nonsmiling between them. Ultimately, however, infant smiling is a constituent of a real-time interactive process and the most appropriate unit of analysis is likely to be dyadic. To understand this process, we begin with an examination of the characteristics of mothers’ interactive smiles. The differences between infant and mother interactive smiling are as revealing as the similarities. When infants engage in higher amplitude smiles and engage in greater eye constriction, they also engage in greater mouth opening. It is not clear, however, whether associations between smile amplitude and mouth opening are as strong as between smile amplitude and eye constriction. To some degree, then, infant smiles appear to involve a single joyful process that is simultaneously indexed by two to three facial indices of emotional intensity. Unlike infants, mothers do not consistently open their mouths to a greater extent when smiling more strongly. Instead, mouth opening in mothers may be used both in coordination with speaking and to make exaggerated visual displays and vocalizations. For example, mothers often repeatedly open their mouths as they draw their head back from infants and then move their head toward the infant and close their mouth in a pattern that often involves vocalizing. In some ways, the caregiver’s role is more complex than that of the infant. Caregivers are expected both to elicit pleasant, ideally positive, engagement from the infant and to respond to the infant joyfully in a fluid fashion.

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C. SMILES AS CONTINUOUS INDICES AND SMILES AS DISTINCT TYPES—A RAPPROCHEMENT? We have suggested that smiles are, on the one hand, discrete communications of qualitatively different engagement states and that, on the other hand, they are continuous signals of the intensity of emotional engagement. How can these views be integrated? A theoretically satisfying synthesis is that qualitatively discrete positive emotional “attractors”—such as a particular type of smiling in a particular interactive moment—may self-organize in response to underlying continuous processes (Chow et al., 2005; Weerth & Geert, 2000). Currently, however, there may be no definitive resolution to this tension. Just as light behaves both as a particle and as a wave (Compton & Shankland, 1973), smiles may function both as discrete indices of specific states of engagement and as flowing indices of positive engagement. It may be productive, at this juncture, to adopt the view of social smiling most conducive to a specific phenomenon or research question while remaining open to the complementary perspective. Vocalizations, for example, tend to be embedded in the course of a smile such that the smile is punctuated by the vocalization (Yale, Messinger, & Cobo-Lewis, 2003; Yale et al., 1999). This may create a qualitatively distinct attention-getting positive emotional expression, or it may serve as an intensifier of facially communicated affect (Hsu et al., 2001).

IV. The Interactive Development of Smiling Whether smiles index a related family of positive emotions or a single emotion of joy, smiling develops within real-time interactions between infants and social partners. In this section, we examine interactive smiling and its development from a dynamic systems perspective. We ask how infants’ smiles are coordinated with mothers’ smiling and with infants’ gazes at mothers’ faces and describe how these patterns develop to usher in the onset of intentional communication. A. OVERVIEW OF INTERACTIVE SMILING Mothers smile more readily than infants. Between 2 and 5 months, mothers’ smiles and other displays such as head nodding and vocalizing are typically necessary to elicit infants’ smiles. But infants frequently do not smile in response to mother. Mothers’ smiles and other displays are not sufficient to elicit infant smiling (Symons & Moran, 1994). An infant smile, by contrast, is typically sufficient to elicit a mother smile. But infant smiles are by no means necessary to elicit mother smiles as mothers often smile in the absence of an infant smile (Cohn & Tronick, 1987; Kaye & Fogel, 1980). When mothers smile in response to

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infants’ smile onsets, they do so within 2 s (Malatesta & Haviland, 1982; Van Egeren, Barratt, & Roach, 2001). Interactive smiles are not series of onsets, but continuous processes. Infant and mother influence not only the onsets of each other’s smiles but the offsets as well. Mothers rarely break off bouts of mutual smiling. Instead, they terminate their smiles only after their infants have stopped smiling. When infants gaze away from mother, they typically terminate their smiles soon after. Thus the infant’s prototypical experience of smiling is smiling with another. During face-to-face interactions, infant smiles are often pursued by mothers and fathers. Fathers tend to employ a more physical style of play with their infants (e.g., bouncing games), whereas mothers rely more on visual and auditory expressive displays to elicit smiles (Dickson et al., 1997). Perhaps as a consequence, infant positive emotional displays with mother build more gradually but positive emotional displays such as smiling appear more suddenly with father (Feldman, 2003). Generally speaking, caregivers use a wide range of stimulating actions in multiple modalities (e.g., variations in vocal intensity and pitch, smile intensity, and moving their faces close to the infant), which facilitates the occurrence of complex, repeated, interactive patterns. Caregivers’ tickling and high-pitched vocalizing, for example, might be followed by an infant smile, the infant gazing away from the caregiver, and a decrease in smiling followed by the infant gazing again at the caregiver. One possibility is that, in some respects, the caregiver’s role in this interactive system is analogous to providing energy in the form of heat to chemical solutions (Hill & Moylan, 1976). The continuous provision of heat can yield a Benard cell that displays repeating, complex, but not entirely predictable, visual patterns (Prigogine & Stengers, 1984). Infant–caregiver play is also an open system in which the caregiver’s positive expressive energy facilitates the emergence of complex, repeating, not entirely predictable interactive patterns. B. THE DEVELOPMENT OF SOCIAL SMILING IN INTERACTIVE CONTEXT Social smiling is typically studied in industrialized societies and typically studied during face-to-face interactions with a parent (see Figure 5). Infants smile for approximately 20% of face-to-face interactions. When observations are conducted on a weekly basis between 2 and 6 months, individual infants typically show stable quantities of smiling in face-to-face interactions (Malatesta et al., 1989). Although approximately one-quarter of the variance in the development of smiling during this period is related to individual differences between infants, the origins and correlates of these differences are not well understood.

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Proportion of Combined Open-Mouth Smiling with Eye Constriction

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Proportion of Simple Smiling Involving Neither Mouth Opening or Eye Constriction

Between 2 and 6 months, infants spend increasing amounts of time smiling (Malatesta et al., 1989, 1986). They become more likely to gaze at mother when she is smiling or creating other facial displays and become more likely to smile in response to maternal smiles (Cohn & Tronick, 1987; Kaye & Fogel, 1980; van Beek, Hopkins, & Joeksma, 1994). Infants’ tendency to initiate smiles—even in the absence of a previous maternal smile—becomes pronounced between 6 and 9 months (Cohn & Tronick, 1987), signaling the infant’s increasingly active, positive participation in the interaction. Most of the types of smiling identified in the previous section arise during multiple periods of face-to-face interaction in the first 6 months of life (Messinger et al., 2001). Simple smiles that involve neither eye constriction nor mouth opening, for example, arise in periods characterized by both the presence and absence of the infant’s gaze at mother’s face and the presence and absence of mother smiling (see Figure 6). This suggests that infants’ use of less affectively intense simple smiling does not become more specific with age. This is surprising as simple smiling, by 12 months of age, predominates during pleasurable but not extremely arousing activities such as book reading (Dickson et al., 1997). In contrast with simple smiling, open-mouth smiling involving eye constriction shows a distinct developmental trajectory. Between 1 and 6 months of age, infants become increasingly likely to use open-mouth smiling with eye constriction— which is almost certainly high-amplitude smiling—to interact with their mothers when their mothers are smiling. They become increasingly less likely to engage in this smiling when they are not gazing at mother and mother is not smiling. In sum, 0.8 0.7 0.6

No Gaze Mother, No Mother Smile No Gaze Mother, Mother Smile Gaze Mother, No Mother Smile Gaze Mother and Mother Smile

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2-3 3-4 4-5 Age Period in Months

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2-3 3-4 4-5 Age Period in Months

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Fig. 6. Open-mouth smiling with eye constriction increases when infants are gazing at their mothers’ faces while their mothers are smiling. It decreases when infants are not gazing at their mothers while their mothers are not smiling. By contrast, smiling with neither characteristic, that is, smiling alone, tends to increase irrespective of where the infant is gazing and whether or not the mother is smiling.

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infants’ increasing tendency to engage their smiling mothers with open-mouth smiling with eye constriction between 3 and 6 months appears to reflect their growing capacity to engage dynamically in intensely joyful interactions. C. SMILING INTERACTION DYNAMICS In interaction, caregiver and infant continuously provide and receive social information, via changes in facial expression, vocal tone, touch, movement, and the direction of infant gaze (Cohn & Tronick, 1987; Feldman, 2003; Feldman & Greenbaum, 1997; Feldman, Greenbaum, & Yirmiya, 1999; Feldman et al., 1996; Fogel, 1988, 1993). To examine interactive emotional influence, we employed the automated measurements of smile intensity in infants and in mothers discussed earlier. As noted earlier, eye constriction and mouth opening were associated in infants, and smile amplitude and eye constriction were associated in mothers. This suggests at the outset that infant’s use of mouth opening in smiles is not directly related to mother’s use of mouth opening. In other words, infants and mothers are not precisely imitating the form of each other’s smiles. In examining how each partner influenced changes in the other’s positive expressions, we identified two initial patterns. One dyadic pattern was characterized by rapidly repeating, tightly linked rises and falls in infant and mother smiling that were punctuated by the mother tickling the infant. Another pattern involved slower, less synchronous rises and falls in infant and mother smiling and a less prominent role for mother tickling. The ultimate goal of this research is to document how each partner influences the rate of change, the actual emotional dynamics, of the other partner’s expressions (Boker & Nesselroade, 2000; Chow, 2005; Rotondo & Boker, 2002). D. INFANTS’ PERCEPTIONS OF INTERACTIVE SMILING Infants’ perceptions of the smiling of others also shed light on the development of positive emotion. Researchers often examine infant smiling within interactive contexts marked by responses to maternal smiles and vocalizations. Rarely, however, is this work integrated with investigations of the conditions under which infants recognize smiles. In fact, however, it is important to explore infants’ comprehension of emotion expressions in an ecological context similar to that in which they communicate using these expressions. By 3½ months, infants gaze longer at a dynamic facial expression (happy or sad) that matches that of a concordantly presented vocalization, even after a brief delay. The effect is present, however, only when the infant’s mother—not an unfamiliar female tester—produces the displays (Kahana-Kalman & Walker-Andrews, 2001; Montague & Walker-Andrews, 2002).

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Contextual information—provided by peekaboo—also appears to facilitate early recognition of smiling expressions (Montague & Walker-Andrews, 2001). When 4-month-olds participate in peekaboo games in which a tester’s happy/surprised expressions are systematically replaced with anger, fear, or sadness expressions, infants show greater interest and surprise and different patterns of visual attention to the discrepant expressions.

V. Smiling and Attention to the Caregiver A. SMILES AND AROUSAL MODULATION Although smiles are approach-oriented signals of enjoyment, infants may also use smiles to manage arousal. Arousal in infants is indexed by increased heart rate and by arousal-modulation activities such as mouthing objects and gazing away from engaging stimuli (Weinberg & Tronick, 1996). As in adults (Cacioppo et al., 2000), an infant’s heart rate is more rapid during smiling than during neutral expressions (Emde et al., 1978). Infants tend to mouth their hands while smiling, suggesting that smiles may be involved in tension reduction. Smiles typically occur while gazing at the caregiver’s face (Weinberg & Tronick, 1994) and this may also may be relevant to infant arousal modulation. Face-to-face visual regard is a relative rarity among nonhuman primates. Among all primates, including humans, face-to-face visual regard can be used a threat display. It is possible, then, that infant smiles can be used to maintain arousing face-to-face eye contact (cf. Morris, 1967). We have, for example, observed smiles to occur in close temporal proximity and even overlap negative emotional expressions. This occurs, for example, as caregivers attempt to “cheer up” infants who have become overexcited in play or are recovering from the still-face perturbation (Weinberg & Tronick, 1996). Documentation of such patterns might suggest that smiles themselves can be used to regulate arousal and that the arousal regulation capacity of infant smiles is sometimes overwhelmed, leading to a negative expression. B. THE EARLY COORDINATION OF SMILING AND GAZING AT THE CAREGIVER’S FACE From a developmental perspective, infants between 2 and 3 months of age occasionally smile at a social partner (sometimes they smile at themselves in a mirror) and then gaze away. Smiles in which infants gaze away before the peak of the smile is reached have been described as communicating a “coy” quality and naïve observers perceive some smiles with these characteristics as indicative of shyness (Draghi-Lorenz, Reddy, & Morris, 2005; Reddy, 2000). The coordination of smiles with gazing changes and becomes more precisely patterned with age (Yale et al., 2003, 1999). Simulation studies suggest that, at

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3 months, the pattern of gazing away during a smile actually occurs less than expected by chance (Yale et al., 2003, 1999). The simulation studies indicate that 3-month-olds tend to begin and end their smiles within the course of a gaze at the parent’s face (Yale et al., 2003). That is, early expressions of positive emotion are dependent on continuous visual contact with the parent. By 6 months, infants redirect their attention after sharing positive emotional expressions with their parents. They tend to gaze at mother’s face, smile, gaze away, and then end the smile. Such gaze aversions—at least among 5-month-olds playing peekaboo—tend to occur during higher intensity smiles and smiles of longer durations (Stifter & Moyer, 1991). It is suggestive that toward 6 months of age infants become especially likely to control their own positive emotion by gazing away from mother during the course of a smile. This is also the period in which infants become adept at using intense open-mouth smiles with eye constriction to participate in highly arousing social situations. Infants are simultaneously becoming more actively positive during interactions and becoming more active at regulating the conditions under which they will become positive engaged (Messinger et al., 2001; Yale et al., 2003).

C. THEORETICAL PERSPECTIVES RELEVANT TO SMILES AND GAZE AVERSION Theoretical perspectives hailing from social psychology may be relevant to infant gaze aversion during smiles. One theoretical perspective holds that positive emotion occurs when an individual attains a goal faster than anticipated (Carver, 2001, 2003). Goals are desired end states. When goals are attained more rapidly than expected and positive emotion occurs, the individual is likely to attend to other features of the environment including other potential goals. This may be partially responsible for the broader, more creative cognitive set of adults after they have experienced positive affect (Fredrickson, 2001; Fredrickson & Joiner, 2002). Although infants’ goals are relatively inchoate, Carver’s (2001, 2003) proposal may be relevant to infant’s proclivity to gaze away from the parent’s face during a smile. Infants are learning to expect peaks and declines in arousal associated with interactive smiling. The infant’s growing tendency to gaze away from the parent’s face during a smile may index the infant’s developing comprehension that an affective climax has been reached; that is, in the most primitive sense, a goal has been achieved. In this sense the infants’ smiling behavior may index the infant’s affective and cognitive comprehension of their interface with the environment at a particular moment (Fogel, Bosma, & Kunnen, 2001).

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VI. Smiling and Referential Communication In this section, we examine infants’ developing capacity to utilize smiles to communicate intentionally toward the completion of the first year of life. In the first 6 months, infant emotional expressions appear to reflect, for the most part, a primary, nonreflective communication of immediate experience (Kaye & Fogel, 1980). Infants engage in intricate communicative smiling exchanges at 6 months, but their smiles are the message. They do not clearly communicate about external events. Surprisingly, the form of infant smiling does not appear to change between 6 and 12 months (Fogel et al., 2006). Instead, it is the timing of smiles and gazes at a social partner that changes as smiles become vehicles for referential communications about external objects and events. By way of backdrop, between 8 and 12 months, infants begin to communicate desires and experiences intentionally to their communicative partners (Adamson & Bakeman, 1985). Infants create conventional or ritualized behavior patterns with the apparent intent of influencing another. Infant smiles are more likely to accompany protodeclarative communication, whose goal is showing or sharing, than protoimperatives, whose goal is obtaining an object or action (Kasari et al., 1990; Messinger & Fogel, 1998). Both smiles and protodeclarative gestures tend to occur in the context of coordinated joint engagement in which the infant actively shifts attention between a toy and a social partner (Adamson & Bakeman, 1985). These gestures and attentional patterns are often referred to as triadic communication in that the infant refers to an object or event outside the infant–partner dyad. Patterns of triadic joint engagement— both those that are accompanied by smiles and those that are not—increase substantially between 5 and 9 months (Striano & Bertin, 2005). Yet the percentage of infants who accompany a gaze between a toy and an adult with a smile is dramatically less than the percentage of infants who only coordinate gazing between the toy and the adult at 5, at 7, and at 9 months. This suggests that combining a smile with a gaze at an attentive adult indexes a more complex communicative achievement than gazing alone. Anticipatory smiles are a specific temporal pattern of smiling and gazing at a partner that may have special intersubjective significance (see Figure 7) (Venezia et al., 2004). Anticipatory smiles occur when an infant smiles at an interesting toy or event and then turns to gaze at another person while continuing to smile. We have studied anticipatory smiles during infant initiations of joint attention in which a tester places a windup toy on a table (Mundy, Hogan, & Doehring, 1996; Seibert, Hogan, & Mundy, 1982). In this context, the infant’s smile while gazing between the object and social partner appears to communicating something like, “that was funny, wasn’t it?”

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Fig. 7. Anticipatory smile. A 15-month-old infant gazes at an object (left), smiles at the object (middle), and gazes at the experimenter while continuing to smile (right).

Developmental and associated evidence suggests infants use anticipatory smiles to communicate preexisting positive affect to another person. Infant anticipatory smiles—whether occurring in interaction with mother or an experimenter— increase between 8 and 12 months. This developmental increase is not seen in rates of initiating joint attention generally or in other patterns of smiling accompanying initiations of joint attention. The degree to which infants engage in anticipatory smiling is associated with separate measures of their level of intentional communication and understanding of means–end relationships (Jones & Hong, 2001). This suggests that, when engaging in anticipatory smiles, infants are coming to understand and refer to the relation of an adult and an object. During anticipatory smiles, infants smile and, in real time, reference an object to another. From a dynamic systems perspective, this real-time process suggests how positive affect may motivate the development of early referential communication (Adamson & Bakeman, 1985; Fogel & Thelen, 1987; Jones & Hong, 2005; Venezia et al., 2004).

VII. Pragmatics: The Representativeness, Discriminant, and Predictive Validity of Infant Smiling This section reviews literature on the representativeness of laboratory studies of infant smiling and differences in smiling between typically developing and atrisk infants. We then examine associations of infant smiling with developmental outcomes. A. REPRESENTATIVENESS OF SMILING Many of the studies reviewed in this chapter occurred in controlled laboratory settings. Interest in developmental outcomes, then, raises questions concerning the stability and representativeness of findings. In Western industrialized societies the quantity of infant smiling coded during the 3-min

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face-to-face interactions with mother typically is correlated with infant affective state observed during 2–3 h home observations (Cohn et al., 1990). Infants’ positive smiling reactions to social stimuli such as peekaboo are associated with observed infant positive emotional tone during interactions with parents and with parent ratings of their children’s day-to-day positive emotions (Aksan & Kochanska, 2004). From a broader perspective, however, frustratingly little is known concerning the frequency and duration of smiling outside of the structured face-to-face interactions that have been observed by researchers in the day-to-day life of infants in industrialized societies. Rates and types of smiling do, however, allow developmentalists to discriminate between typically and atypically developing infants. B. SMILING IN ATYPICALLY DEVELOPING INFANTS Patterns of smiling allow us to distinguish typically developing infants from infants at risk for different types of disturbed development. Infants at risk for autism exhibit lower levels of smiling than typically developing infants (Cassel et al., 2007 Zwaigenbaum et al., 2005). Maternal depression and maternal depressive symptomatology, particularly when chronic, tend to be associated with less frequent infant smiling, at least during interactions with mother (Moore et al., 2001). Smiles are more frequent among healthy infants than among those with a history of neurological complications or other illnesses related to preterm birth (Bigsby et al., 1996). Infants at risk for developmental difficulties also show deficits in particular types of smiling. Premature infants, for example, engage in lower levels of high amplitude and/or open-mouth smiling during face-to-face interactions and exhibit fewer high-amplitude smiles during peekaboo games with a trained experimenter than do full-term infants (Eckerman et al., 1999; Segal et al., 1995). This difference is likely due to premature infants’ reduced capacity to tolerate highly arousing positive affect. An opposite pattern is seen in infants with Down syndrome. These infants show a pattern of somewhat indiscriminate intense smiling. They tend to direct smiles with eye constriction and mouth opening both to the toys with which they are playing and to their mothers, whereas typically developing infants direct these smiles only to their mothers (Berger & Cunningham, 1986; Carvajal & Iglesias, 2002). C. SMILING AND DEVELOPMENTAL OUTCOMES Still-face studies are often the basis for investigations of the predictive validity of early smiling. Individual infants show consistency in smiling levels over the episodes of face-to-face/still-face, particularly between the interactive face-to-face

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and reunion episodes (Carter, Mayes, & Pajer, 1990; Cassel et al., 2007; Moore et al., 2001; Weinberg et al., 1999). Surprisingly, smiling at the still-face does not increase after 1½ months of age (Bertin & Striano, 2006; Lamb, Morrison, & Malkin, 1987), nor does it show developmental stability within infants (Moore et al., 2001). The possibility that smiles during the still-face can be positively characterized as bids for the parent’s attention deserves increased attention from researchers. There is some evidence that infant smiling in the face of the challenge of the parental still-face may index emotional resilience. Six-month-old infants who smile during the still-face are more likely to become securely attached at 12 months than infants who do not (Cohn, Campbell, & Ross, 1991). They are also perceived by their parents as having fewer externalizing behaviors at 18 months than infants who did not smile during the still-face (Moore et al., 2001). Still-face smiling may reflect an infant’s expectations of positive communication and be associated with dyadic patterns of harmonious interaction that subsequently lead to more optimal developmental outcomes. Positive affect sharing indexed by anticipatory smiling may be one link between early social smiling and subsequent social expressivity and competence (Parlade, Messinger, & Mundy, 2006). Smiling by 6-month-olds in face-to-face interaction with a parent and in the subsequent still-face positively predicts mean levels of anticipatory smiling with a tester between 8 and 12 months. An infant’s experience with early gratifying social interaction probably contributes to a continued tendency to share positive affect with an adult. In fact, affectively positive infant joint attention communications are, more generally, predicted by highly sensitive maternal caregiving (Hane & Fox, 2006). In addition, mean levels of anticipatory smiling predict parent-reported social expressivity and social competence at 30 months (Parlade et al., 2006). Infants who share smiles with relatively unfamiliar adults may be more motivated than other infants to engage socially and emotionally with others. Researchers motivated by a positive psychology perspective have become involved in investigating the impact of positive emotions—above and beyond the absence of negative emotion—on interpersonal competence and well-being. Positive emotional experience in infants may, as in adults, broaden the scope of attention and the behavioral repertoire and elicit positive responses from social partners (Fredrickson, 2001; Fredrickson & Joiner, 2002; Harker & Keltner, 2001). One longitudinal study relied on an extreme groups design in which infants were selected based on their emotional reactions to neutral stimuli at 4 months of age (Fox et al., 2001). Infants who engaged in more smiling, neutral/positive vocalizations and motor movement were compared to infants who had negative reactions or were not responsive to the stimuli. The infants who showed earlier emotional positivity exhibited less behavioral inhibition in unfamiliar situations over the first 2 years of life than other infants. They continued to show a more exuberant temperamental style at 4 years when they were

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more likely to talk and engage with peers (Fox et al., 2001). Similar results have been reported among a normative sample of 18-month-olds observed during reunions with mother in the Strange Situation (Abe & Izard, 1999). Infant smiling involving eye constriction (Duchenne smiling) predicted parent ratings of extraversion and openness to experience when children were 3½ years of age. Smiling interactions involve coconstructing processes of responsive engagement. Relationships characterized by this mutual positivity may have relatively enduring developmental effects. Caregiver positive emotional responsivity to the infant is associated with later internalization of social norms and committed compliance to maternal requests (Kochanska, 2002; Kochanska, Forman, & Coy, 1999). Experiences of affectively positive responsivity, participation in the ebb and flow of joyful engagement, may enable infants to experience their own joy as a mutual process. Joy is not only shared but created in such interactions. The delight of engaging in a positive process bounded by mutual expectations ultimately contributes to the creation and internalization of social norms.

VIII. Summary and Conclusions Infant smiles emerge even in the absence of visual feedback, but their interactive development and intensification appear to be dependent on experiences of visually mediated interaction. Although neonatal smiling has no clear emotional content, social smiling emerges out of attentive engagement with an interactive caregiver. This process illustrates the dynamic systems postulate that real-time interaction is a window on developmental process. On the one hand, specific dimensions of smiling may have qualitatively different psychologically meanings. On the other hand, different features of infant smiling may reflect linked indices of a single dimension of positive emotion that ebbs and flows in time. The resolution of this paradox will likely involve continued attention to the interactive flow of positive emotion communication. This will be facilitated by new methods for measuring smiling and positive emotion in time. Smiling may simultaneously index a desire to interact and the dissipation of arousal associated with that interaction. Infants’ capacity to become actively and vigorously caught up in emotionally positive smile-mediated interaction is linked to their ability to regulate that emotion by gazing away from their interactive partners. Ultimately, this attentional control paves the way for infant’s tendency to use smiles to initiate early referential communication with a partner. These anticipatory smiles may provide a developmental bridge between early emotionally positive dyadic responsivity and later patterns of social competence.

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Author Index

A

Andrews, J., 126 Andrews, P., 6 Angeli, S. J., 62 Anglin, J., 300, 302, 318 Anisfeld, E., 334–336 Antill, J. K., 181, 183, 191 Apel, K., 147 Arbreton, A., 188 Archibald, L., 148 Ardila-Rey, A., 185, 190, 192 Arnbak, E., 319 Aronson, J., 189, 200 Arsenio, W. F., 208 Askew, J., 201, 203 Atkinson, R. C., 43 Ayers, M., 194

Aarnouste, C., 309 Abbott, R., 307, 314, 317 Abbott, S., 307 Abe, J. A. A., 329, 357 Aboud, F. E., 176, 194–197, 200 Abrams, D., 173–175, 177, 206 Achenbach, T. M., 262 Achilles, C., 269, 271–272 Ackerman, B. P., 329 Acosta, S., 339–340, 345, 355–356 Adam, G., 162 Adams, C., 140 Adamson, L. B., 342, 353–354 Addis, D. R., 49 Adlam, A. R., 53 Adlof, S., 140 Agentta, B., 8 Aggleton, J. P., 60 Aicardi, J., 49 Ainsworth, M. D. S., 90, 96, 98, 101 Akinson, L., 96, 119–120, 125–127 Aksan, N., 355 Alarcon, O., 177 Albert, P., 60 Alberts, D., 275 Albin, M., 349 Alegria, J., 311 Alexander, K. L., 276 Allan, S., 105, 120, 126 Allen, J. P., 264 Allen, J., 53 Allen, W. R., 202 Allport, A. D., 234 Allport, G. W., 195, 204 Alpert, A., 126 Als, H., 13, 342 Alvarado, M. C., 51, 62 Alvarez, P., 47 Amato, M., 197 Ambadar, Z., 339–340, 345 Ancoli, S., 343 Anderson, R. C., 302–303, 306, 314 Andrade, J., 222

B Baayen, R. H., 301, 303, 305 Babb, S. J., 54 Bachevalier, J., 39, 51, 58–59, 62 Bachman, H. J., 277–278, 286 Bachorowski, J.-A., 339 Baddeley, A. D., 49, 147–148, 221–226, 231, 235, 237–238, 242–243, 246 Bahrick, L. E., 334 Bakeman, R., 353–354 Baker, S., 225 Bannister, L. H., 330, 344 Barash, D. P., 20 Barbarin, O., 270 Barber, B., 188 Bard, K. A., 329, 339 Barnes, E. J., 202–203 Barnier, A. J., 44 Baron, J., 301, 309 Baron-Cohen, S., 7–10 Barr, R., 53 Barratt, M. S., 348 Barrett, H. C., 15–16 Barrett, K. C., 93, 329 Barrett, L. F., 113, 328, 331, 341 Barrouillet, P., 234, 239, 243, 311 Bartholomew, K., 121, 128 367

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Author Index

Bartke, S., 143 Bartko, W., 183, 191 Basque, M., 312, 316, 318 Bates, E. A., 71, 155, 301 Bates, J. E., 280 Battel, J., 149 Bauer, P. J., 38–39, 53, 69 Bauer, R. M., 44 Baumann, J. F., 309 Bavin, E., 148 Bayliss, D. M., 221, 231, 237–238, 242–243 Beardslee, W., 106–107 Bedore, L., 141, 144–146, 152–153, 155 Beghi, A., 333–334, 340 Bell, D. C., 94, 106 Belsky, J., 5, 19, 29, 115, 124 Bennett, C., 186 Bennett, R. T., 63 Berends, M., 271 Berger, J., 355 Berliner, D. C., 263–264 Bernadin, S., 234, 243 Bernal, M., 202–203 Berninger, V., 221, 307, 314, 317 Berntson, G. G., 351 Berridge, K. C., 7 Bertin, E., 353, 356 Bertram, R., 311 Betts, J. R., 271 Bhatt, R. S., 53 Bierman, K. L., 174 Biernat, M., 182, 190 Bigelow, A. E., 337 Bigler, R. S., 176–177, 190, 206 Bigsby, R., 355 Bindman, M., 310, 314, 317, 321 Bird, A., 69 Biringen, Z., 184 Bishop, A., 203 Bishop, D. V. M., 140, 152, 155, 235 Bittle, M. L., 185 Bittner, G. D., 2–3 Bjorklund, D. F., 1–2, 6–7, 9, 12, 15–17, 23, 25, 29, 45 Black, J. E., 13–14, 17, 21, 23, 71 Black, M. P., 18 Blackwell, A., 155 Blair, S. L., 183 Blatchford, P., 269, 271 Blatz, W. E., 90

Blaxton, T. A., 44 Blehar, M. C., 90 Bleske, A., 94 Bloodworth, M. R., 280 Blumenfeld, P., 188 Bock, K., 150–151 Bodison, P., 203 Boesch, C., 8 Bogner, K., 256, 263, 267 Bohbot, V. D., 60, 62 Boker, S. M., 347, 350 Boland, L. D., 42 Bolduc, D., 185 Bolling, L., 61 Bolzani-Dinehart, L., 339–340, 345 Bonar, C., 329, 339 Bond, J. T., 182 Bond, N. W., 108, 111 Boniface, J., 53 Bortolini, U., 144–145 Bosma, H. A., 352 Boulton, M. J., 194 Bowe, K., 243 Bowlby, J., 90, 93, 98, 111, 120, 335 Bowman, P. J., 203 Boyce, W. T., 2–3, 19, 115 Boykin, A. W., 202 Bradley, R., 265, 281 Branch, C. W., 202 Brandimonte, M. A., 222, 235 Bransford, J. D., 264 Brazelton, B., 342 Bremner, J. G., 61 Brenick, A., 199 Bretherton, I., 90, 93, 96 Breton, C., 9 Brewer, D. J., 269, 271–273 Brewer, M. B., 200 Brewer, W. F., 45 Brian, J., 355 Bridges, K. M. B., 328 Bridges, L. J., 332 Briggs, R. J., 271 Brittain, M. M., 316 Broadbent, D. E., 229 Brooks-Gunn, J., 255, 288 Brophy, J., 263–264, 275 Brotman, M. A., 184 Brough, S., 126 Brown, A. L., 61, 264

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Author Index Brown, C. B., 177, 206 Brown, D., 184, 355 Brown, F. H., 6 Brown, G., 233 Brown, K., 174, 177 Brown, R. W., 60 Browne, W., 271 Bruce, D., 43 Bruce, V., 70 Bruck, M., 313 Bruner, J. S., 24, 27 Brunswik, E., 22 Bryant, D., R., 270 Bryant, F. B., 277 Bryant, P., 310–311, 314, 316–317, 319, 321 Bryson, S., 355 Buchman, A., 355–356 Buckner, J. P., 184 Buckwalter, P., 139, 147 Bugental, D. B., 2, 29 Buhs, E. S., 278 Bukowski, W., 174, 188, 198, 203 Buller, D. J., 1 Bumpus, M. F., 183 Burani, C., 303 Burgess, K. B., 280, 282 Burgess, N., 49, 60, 66 Burgess, R., 1–2, 16 Burkam, D. T., 267 Burk-Braxton, C., 201 Burman, B., 88 Burnett, P. C., 264 Burrows, A., 329, 339 Burton, A. M., 70 Bush, N. F., 128 Bushnell, E. W., 61 Buss, D. M., 4–5, 16, 94 Buss, K. A., 332 Bussey, K., 186 Byng-Hall, J., 106, 121, 128 Byrd, T., 193 Byrne, B., 55

C Cabeza, R., 50 Cacioppo, J. T., 351 Calkins, S. D., 129, 356–357 Call, J., 8 Cameron, C. E., 264

Cameron, L., 177 Camos, V., 234, 239, 243 Campanella, J., 53 Campbell, L., 5 Campbell, M. E., 196, 204 Campbell, S. B., 124, 280, 342, 355–356 Campbell, T., 147 Campos, J. J., 93, 329, 332–333, 351 Campos, R. G., 93, 329 Camras, L. A., 329 Capaldi, D. M., 121, 127 Caplan, D., 232 Caplow, T., 182 Caporael, L., 1 Carlisle, J. F., 298–302, 305–308, 310, 313–317, 319–320 Carlson, E. A., 128 Carlson, S. M., 9 Carman, H. M., 60 Carney, E., 148 Carpenter, M., 27 Carpenter, P. A., 224, 226, 240 Carroll, M. V., 55 Carter, A. S., 356 Carvajal, F., 355 Carver, C. S., 352 Casalis, S., 314, 316, 319 Case, R., 226–228, 239, 241, 246 Caselli, M. C., 144 Caspi, A., 3, 121, 127 Caspi, B., 355 Cassar, M., 310 Cassel, T., 339–340, 345, 355–356 Cassidy, J., 90, 98, 101 Castaneda-English, P., 201, 203 Castel, A. D., 67 Castellanos, F. X., 51 Catts, H., 140, 147 Ceder, I., 177 Cezayirli, E., 60 Chalfonte, B. L., 66–67 Champion, K., 105, 118 Chance, M. R. A., 125 Chance, S., 110 Channon, S., 62 Charest, M., 163–164 Charlesworth, W. R., 2 Chase, N. D., 121, 128 Chatters, L. M., 202 Chavira, V., 201–202

369

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Author Index

Chee, M. W. L., 51 Chen, C., 276 Chen, L., 202–203 Chen, Y. R., 201 Cheung, H., 316 Chiappe, D., 7 Chiu, C. Y., 198 Cho, J.-R., 316, 318 Choi, L., 316 Chow , C. S.-L., 316 Chow, B. W.-Y., 314, 316–318 Chow, S. M., 345–347 Christal, R. E., 221 Christian, K., 277 Christianson, K., 304, 320 Chun, J., 271 Church, B. A., 55 Churchland, A., 59 Chynoweth, J., 147 Cicchetti, D., 88, 90, 94, 105–106, 113, 116, 118–119, 121, 123–124 Clahsen, H., 146 Clark, E. V., 302, 311 Clark, M. L., 185, 194 Clarkin, J., 124 Clarkson, M. G., 57 Clayton, N. S., 53–54 Clearfield, M. W., 61 Cleave, P., 146 Clement, T. S., 53 Clifton, R. K., 57 Clore, G., 347 Clotfelter, C. T., 256–257, 266, 269–270, 272–273 Cobb, H., 153 Cobb, N. J., 197 Cobo-Lewis, A. B., 347, 351–352 Cocking, R. R., 264 Cohen, D. J., 124 Cohen, H., 316, 318 Cohen, J., 274 Cohen, M., 355 Cohen, S. R., 302 Cohn, J. F., 339–340, 342, 345–347, 349–350, 355–356 Cole, P. M., 105, 118 Colé, P., 303, 316 Colle, M., 333 Collins, M., 273 Colom, R., 221

Coltrane, S., 182 Columbus, R. F., 13 Compton, A. H., 347 Conger, R. D., 177 Connell, J. P., 255 Connell, S., 61 Connor, C. M., 264, 272, 277–278, 282, 286 Connor, R., 282, 288 Constable, R. T., 49 Conway, M. A., 46, 50 Cook, M., 26 Cook, T., 288 Cooper, H. C., 182 Cooper, J. J., 50 Cooperman, J., 123 Copeland, D. E., 225 Coppola, M., 25 Corkin, S., 48 Cormier, P., 311 Cornoldi, C., 224 Cosmides, L., 2–5, 7, 15–16, 28, 47, 94–95, 110 Cossette, L., 185 Coster, W., 355 Cota, M., 202–203 Cotton, J., 181, 183, 191 Courage, M. L., 39, 69–70, 72 Cowan, C. P., 277–278 Cowan, N., 147, 224, 230, 232–233, 242 Cowan, P. A., 277–278 Cox, M. J., 121, 128, 265, 273, 280–281 Coy, K. C., 357 Craig, I. W., 3 Craik, F. I. M., 63, 67 Crawford, C. B., 94 Crawley, A. P., 49 Crawley, R. A., 42 Crews, D., 19 Crittenden, P. M., 102 Crockenberg, S. B., 107, 113 Crosnoe, R., 280 Cross, W. E., 201 Crouter, A. C., 183, 191 Crovitz, H. F., 41 Crowther, H. L., 61 Cruess, L., 59 Crystal, D., 198–200 Crystal, J. D., 54 Culver, C., 348–349

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Page 371

Author Index Cummings, E. M., 88, 90–91, 93–94, 99, 103, 105–108, 110, 112, 116, 119, 122–124 Cummins, D. D., 23 Cummins, R., 23 Cunningham, C. C., 355 Curtiss, S., 25 Cutrona, C., 177

D D’Esposito, M., 50–51, 67 Dabholkar, A. S., 51 Dagher, A., 60 Daher, M., 332 Dallas, M., 44 Daneman, M., 224, 226, 240 Darling-Hammond, L., 269 Daum, I., 62 Davey, M., 201, 203 Davidson, M., 26 Davidson, R. J., 331, 338, 346 Davies, L., 88 Davies, P. T., 88, 91, 93, 99, 103, 105–108, 112–113, 116–120, 122–124, 127–128, 340 Davis, B., 126 Davis-Kean, P., 181 Dawkins, R., 28 Dawson, G., 338 De haan, E. H., 44 de Haan, M., 48–49, 53 de Jong, J., 143 De Renzi, E., 223 De Souza Silva, M. A., 54 Deacon, S. H., 310, 314, 316–317 Deaux, K., 182 Dedo, J. Y., 329 Deevy, P., 143, 146, 149–150, 163–164 Deklyen, M., 127 DeLeonardis, D. M., 70 Delgado, E. F., 342 Delis, D., 51 Della Sala, S., 222 DeLoache, J. S., 27, 61 Deming, M. P., 121 Dempster, F. N., 225 Denne, T. C., 197 Denton, K., 276 Dere, E., 54 Derwing, B. L., 299 Deutsch, F. M., 191

Devine, P. G., 184, 195 Dewhurst, S. A., 222 Diamond, A., 59 Dickinson, A., 53–54 Dickson, K. L., 329, 339–340, 342, 344, 348–349, 352 Didow, S. M., 69 Diekman, A. B., 206 DiPerna, J., 274 Dixon, A. K., 105, 111, 118–120 Dixon, J., 174 Dobrowolska, O., 340 Dodge, K. A., 280 Doehring, P., 353 Dolan, A., 43 Dolezal, S. E., 267, 276, 284 Dollaghan, C., 147 Domnick, M., 193 Dondi, M., 333–334, 340 Donnett, J. G., 60 Dosher, B. A., 44 Dougherty, L. M., 339 Douglas, S., 182 Dovidio, J. F., 181, 199 Dow, G. A., 53 Dowden, A., 53 Downer, J. T., 260, 270, 277, 285 Doyle, A., 195 Draghi-Lorenz, R., 351 Draper, P., 5, 19 Dromi, E., 162 Drop, S. L. S., 21 Drummey, A. B., 55–57, 60–61, 64, 68, 72 DuBois, D. L., 177, 201 Duchenne, G. B., 337 Dufault, C., 227 Duff, S., 236 Duggan, S., 108 Dukewich, T. L., 99, 112 Dunbar, R. I. M., 339–340 Duncan, G. J., 255, 272, 288 Duncan, J., 222 Dunn, J., 88 Durkin, K., 200 Durrant, R., 5–6 Durrheim, K., 174 Durston, S., 55 Dykes, J., 143 Dyson, M., 330, 344

371

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372

Page 372

Author Index

E Eacott, M. J., 42 Eagly, A. H., 206 Eaker, D. G., 201, 203 Eccles, J. S., 181, 188–189, 193, 264, 288 Eckerman, C. O., 69, 355 Eddy, T. J., 8 Edelman, G. M., 12 Edison, S. C., 72 Edmonds, C., 195–196, 200, 203 Edmonds, S., 271 Edwards, E. C., 309 Edwards, J., 147 Edwards, L., 17 Egan, J., 308 Ehrenberg, R. G., 269, 271–273 Ehri, L. C., 298, 305 Eilers, R. E., 25, 347 Eisenberg, S., 143 Ekman, P., 338, 343, 346 Elbro, C., 319 Elder, G., 280, 288 Elliot, H. C., 330 Elliott, E. M., 230 Elliott, S., 262 Ellis Weismer, S., 140, 142, 147–148, 165 Ellis, B. J., 1–3, 5–6, 12, 15–16, 19–20, 29, 115 Ellison, P. T., 20 Elman, J. L., 71 El-Sheikh, M., 105–107, 116, 119 Emde, R. N., 121, 184, 333–334, 351 Emery, L. J., 227 Emery, R. E., 90, 127 Emslie, H., 222 Endriga, M. C., 127 Engle, R. W., 221, 224–225, 231, 233, 244 Englund, M., 186 Entwisle, D. R., 276 Erel, O., 88 Erkut, S., 177 Esbensen, B. M., 63 Escobar, J., 345 Espelage, D. L., 198 Esteves, F., 26 Evans, J., 147 Eva-Wood, A., 320 Everitt, B. J., 62 Eyer, J., 141, 152–153, 155

F Farrell, D., 99, 112 Farris, E., 280 Farvolden, P., 105, 117, 120 Fayol, M., 301, 304, 311–312 Fearon, R. M. P., 124 Feldman, R., 348, 350 Fenton, R. E., 194, 201 Ferdinand, R. F., 128 Fernandez, O., 227 Ferstl, R., 61 Field, T., 334 Fields, J. P., 177 Fincham, F. D., 88, 90, 107, 113 Finn, J. D., 269, 271–272 Fish, L. S., 201, 203 Fishbein, H. D., 195 Fisher, C. B., 194, 201 Fisher, C., 55 Fiske, K. E., 42 Fivush, R., 39, 62, 69, 184 Flanagan, A., 256–257 Fleagle, J. G., 6 Fleeson, J., 95 Fleming, J., 300–301, 314, 316, 320 Fletcher, P., 142, 152 Flykt, A., 26 Fogel, A., 329, 331, 333–337, 339–340, 342–344, 347–350, 352–354 Foley, R. A., 6 Font, G., 309 Foorman, B. R., 288 Forman, D. R., 357 Forman, E. M., 103, 106–107, 116, 118–120, 122, 127–128 Foster, K. A., 61 Fowler, A. E., 307, 315–316, 318, 320 Fox, H. H. A., 356–357 Fox, N. A., 55–57, 70, 331–332, 338, 356 Frackowiak, R. S. J., 60 Fraiberg, S., 332 Francis, D., 165 Frank, M. G., 346 Franklin, A., 61 Frazier, N., 55 Fredrickson, B. L., 352, 356 Freedman, D. G., 332 Freedman-Doan, C., 188 Freese, P., 140

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Author Index Freud, S., 38 Freyd, P., 301, 309 Frick, J. E., 342 Fridlund, A. J., 329 Fried, C. B., 200 Friedman, B. X., 2–3 Friedman, N. P., 238, 240 Friesen, W. V., 338, 343, 346 Frith, C. D., 49, 60 Frith, U., 9 Fritz, J., 93 Fry, A., 165 Fuegan, K., 182 Fujita, F., 347 Fullinwinder-Bush, N., 128 Furst, A., 246 Furstenberg, F., 288

G Gabriel, R., 47 Gadian, D. G., 48–49 Gaensbauer, T. J., 333, 351 Gaertner, S. L., 181, 199 Gaines, C., 203 Galinsky, E., 182 Gallup, G. G. Jr., 50, 72 Gambone, M. A., 255 Gamoran, A., 269, 271–273 Ganchrow, J. R., 332 Garcia O’Hearn, H., 99–100, 107 Garcia, J., 26 Garcia-Coll, C., 177 Gardner, R., 126 Garman, M., 142 Garmezy, N., 110 Garnier, H., 264, 276 Gathercole, S. E., 147–148, 222, 224–225 Geary, D. C., 2, 7, 9, 18, 23–25, 29 Geert, P. V., 347 Gemar, M., 109 Gentry, B., 147 Gerber, E., 151, 163–164 German, T. P., 47 Germino-Hausken, E., 276 Ghera, M. M., 332 Giedd, J. N., 51 Gilbert, J., 119 Gilbert, P., 96, 103, 105, 111, 115, 117, 119–121, 123, 125–126, 129

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373

Gilboa, A., 48–49 Gillam, R., 147–148, 165 Gluck, M. A., 62 Goeke-Morey, M. C., 99, 107, 112, 116, 122 Goetsch, V., 106–107, 119 Goh, J. O. S., 51 Goldberg, J., 226–228, 239, 241, 246 Goldhaber, D. D., 269 Goldsmith, H. H., 332 Goldstein, R. F., 355 Goldstein, S., 334 Good, C., 200 Good, T., 263–264, 275 Goodman, S. H., 184 Goodnow, J., 181, 183, 191 Gootman, J. A., 264 Gopnik, A., 63 Gottlieb, G., 10–13, 19 Grady, C. L., 49 Graf, P., 55, 63 Graham, S., 174, 198–199 Granger, D. A., 123 Grant, S., 223 Grant, V. V., 42 Graue, M.E., 274 Graves, M. F., 309 Gray, J. A., 62, 108 Green, J. T., 62 Green, L., 320 Green, M., 61 Greenbaum, C. W., 350 Greenbaum, J. L., 55 Greenberg, D. L., 50 Greenberg, M. T., 94, 127 Greene, E. J., 19, 46 Greenough, W. T., 13, 17, 21, 23, 71 Greenwald, R., 272 Greig, R., 201 Greiling, H., 5 Grela, B., 141, 150–153, 155, 163–164 Gresham. F., 262 Greve, K. W., 44 Griffith, E., 275 Griffith, J., 200 Grigoryev, P., 349 Grimm, H., 143 Grissmer, D., 256–257 Grober, M. S., 18 Gross, J. J., 93 Gross, M. R., 19

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Page 374

Author Index

Grossman, K. E., 125 Grube, D., 227 Grych, J. H., 88, 90, 107–108, 113 Guner, B. M., 332 Gunn, D. M., 221, 231, 237–238, 243 Gutchess, A., 51 Gutierrez-Clellan, V., 145

H Haarman, V., 305 Haberlandt, K., 243 Haddock, C. K., 315 Haden, C. A., 69 Haines, E., 182 Hale, S., 165, 227 Hall, M., 224 Halliday, M. S., 221, 225, 230 Halliday, S., 225 Hallinan, M. T., 194–196, 204 Haltigan, J. D., 345–346, 355–356 Hamilton, Z., 228–232, 236 Hamm, J. V., 203 Hammond, H. K., 309 Hamre, B. K., 260, 264–265, 270, 278, 282, 285 Hancock, P. J. B., 70 Hane, A. A., 332, 356 Hansell, N., 68 Hansson, K., 143–144, 146 Hanushek, E. A., 257, 270–271, 273 Harackiewicz, J. M., 42 Harbluk, J. L., 50, 63–64 Hardesty, J. L., 201 Hare, B., 8 Harker, L., 356 Harkness, K. L., 109–110 Harmon, R. J., 333–334 Harnishfeger, K. K., 9 Harold, G. T., 107, 116, 122 Harold, R. D., 188 Harrington, H., 3, 121, 127 Hartley, T., 49 Haselton, M. G., 94 Hasher, L., 232 Hashtroudi, S., 47, 65 Hass, R. G., 195 Hasselhorn, M., 227 Hastings, C. N., 264, 276 Hauck, W. E., 197

Hauerwas, L. B., 307, 314, 316 Hauske, E., 273 Haviland, J. M., 348 Hayden, M., 59 Hayes, S. M., 48–50 Hayiou-Thomas, M., 155 Hayne, H., 42, 53, 70 Head, M. R., 183 Heaviside, S., 280 Hebrank, A., 51 Hecht, S. A., 232 Hedges, L. V., 271–272 Hegley, D., 339 Heinrichs, N., 109, 111–112, 117, 123 Hellewell, T. B., 13 Helwig, C. C., 176 Hembree, E. A., 339 Henderson, A. J. Z., 121, 128 Hendry, L., 225 Henry, L. A., 237 Henry, M. K., 320 Hernández Blasi, C., 16 Hershberger, S., 164 Hertenstein, M. J., 329 Hertsgaard, L. A., 53 Herzog, A., 61 Hesketh, L., 147 Hess, U., 343 Hesse, K. D., 319 Hevenor, S. J., 49 Hicks, L., 182 Hilburn-Cobb, C., 96, 98, 100, 102, 105–106, 121 Hill, D., 348 Hill, K., 6 Hindman, A., 272, 282 Hirsch, B. J., 177 Hitch, G. J., 220–232, 233–236, 240–244, 246 Ho, M.-W., 10 Hoeffner, J., 155–156 Hoffer, D., 307 Hoffman, H. G., 66 Hoffman, L. W., 148, 165, 191 Hofmann, S. G., 109, 111–112, 117, 123 Hofvander, Y., 21 Hogan, A. E., 353 Hogan, T., 140 Hogg, M. A., 173–175, 206 Hogrefe, G. J., 63 Holdstock, J. S., 58, 60

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Page 375

Author Index Holland, A., 151, 163–164 Holt, S. A., 329 Honeycutt, H., 15 Hong, H.-W., 354 Hong, Y. Y., 198 Hopkins, B., 349 Hopkins, J., 355 Hopkins, R. O., 52, 62 Hops, H., 126 Horn, S., 187, 197, 208 Horohov, J., 141 Horton, N., 230, 243 Houston, J. P., 54 Houston-Price, C. M. T., 221, 237 Houts, R. M., 121, 128 Howard, C., 203 Howe, M. L., 38–39, 69–70, 72 Howell, W. G., 271 Howes, C., 194 Hsieh, L., 154 Hsu, H.-C., 339–340, 342–344, 347, 353, 355 Hu, C., 345–346 Hua, S., 307 Hudson, J. A., 62 Huffman, K. J., 7, 23–24 Hughes, C., 9 Hughes, D., 202–203 Hulme, C., 225, 233 Hunkin, N. M., 58 Hunt, C. J., 199 Hunt, R. H., 55 Hupbach, A., 55 Hupet, M., 311 Hurtado, A. M., 6 Hurtado, M., 332 Hutt, R., 69 Huttenlocher, J., 60–61, 72 Huttenlocher, P. R., 51, 334 Hutton, U. M. Z., 221, 227–232, 234, 236, 240, 242–243 Huttunen, M., 117 Hwang, M., 148 Hyde, J. S., 184

375

Ingham, R., 142 Irons, W., 6 Isaac, C. L., 58, 60 Ito, T. A., 351 Izard, C. E., 329–330, 339, 357

J Jackson, J. J., 2–3, 115 Jacobs, J. E., 181, 188 Jacobs, W. J., 5, 61 Jacobvitz, D. B., 100, 128 Jacoby, L. L., 44 Janowsky, J. S., 63 Jarrold, C., 221, 231, 237–238, 242–243 Jarvikivi, J., 311 Jenkins, J. R., 301–302 Jernigan, T. L., 51 Joanisse, M. F., 156, 308 Joeksma, J. B., 349 John, R. S., 99–100, 107 Johnson, D., 202 Johnson, J. S., 25 Johnson, K. A., 271 Johnson, M. B., 262 Johnson, M. D., 43 Johnson, M. H., 13, 70–71 Johnson, M. K., 46–47, 50–51, 65–67, 70, 280 Johnson, R. L., 304, 320 Johnston, J. R., 103, 113, 129 Johnston, J., 141–142, 147–149, 165 Johnston, T. D., 17 Joiner, T., 352, 356 Jolly, C., 125 Jones, D. M., 222 Jones, M., 147 Jones, N. K., 299, 315 Jones, R., 128 Jones, S. S., 354 Jozefowicz, D., 188 Juan-Espinosa, M., 221 Juelis, J., 320 Jurkovic, G. J., 106, 128 Juvonen, J., 174, 198–199

I K Iaria, G., 60 Ibanez, L., 355–356 Iglesias, J., 355 Ikeda, S., 123

Kabbani, N. S., 276 Kafer, K., 271 Kagan, J., 40

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376 Kahana-Kalman, R., 350 Kail, R., 147–148, 165, 228 Kain, J. F., 257, 270, 273 Kalina, M., 60, 62 Kame’enui, E. J., 309 Kamhi, A., 141–142, 147 Kanade, T., 345 Kane, M. J., 221 Kao, G., 195–196 Kaplan, H., 6 Kappas, A., 343 Karmiloff-Smith, A., 71 Kart-Teke, E., 54 Kasari, C., 353 Kasius, M. C., 128 Katz, I., 195 Katz, L. A., 306–307 Katz, L. F., 112 Kawakami, K., 334 Kawata, J., 256–257 Kaye, K., 340, 347, 349, 353 Keating, D.P., 288 Keating, P., 308 Keenan, J. P., 50, 72 Keil, K., 49 Keir, R., 26 Keller, C. V., 233 Keller, M. C., 116, 126 Keller, T. A., 233 Kelly, M. C., 198, 200 Kelson, S., 311 Keltner, D., 93, 184, 356 Kemp, N., 316 Kennedy, J. K., 108 Kennedy, R., 208 Kenny, P., 13 Kensinger, E. A., 48 Kermoian, R., 93, 329 Kernberg, O., 124 Kesner, R. P., 52, 62 Kihlstrom, J. F., 42 Kilborn, K., 155 Killeen, P. R., 230 Killen, M., 173–174, 176–177, 179, 183, 185–186, 188, 190–192, 195–200, 203, 205, 207 Killinger, W. A., 42 Kim, H. K., 121, 127 Kim, J., 186 Kimble, D. P., 62 King, J. A., 49

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Author Index King, J., 66 Kipp, K., 9 Kirby, J. R., 314, 316–317 Kirchner, D., 147 Kirkham, N. Z., 59 Kirsner, K., 55 Kita, S., 25 Klatsky, R., 147 Kleck, R. E., 343 Klein, S. B., 47 Klein, S., 110 Klem, A. M., 255 Klinger, L. G., 338 Klock, K., 201, 203 Klockow, L. L., 108 Kloska, D. D., 191 Knight, G., 202–203 Kobrynowicz, D., 182, 190 Kochanska, G., 355, 357 Kocinski, D., 225 Koelling, R. A., 26 Koenig, K., 333 Kolodny, J., 222 Konstantopoulos, S., 271 Koogmans, H. J., 43 Koterba, S., 345–346 Koutstaal, W., 66 Kovacs, S. L., 58, 67–68, 70 Kraemer, P. J., 60 Krogh, H. R., 190 Krohn, T., 243 Krueger, A., 272–273 Ku, Y.-M., 314 Kulkofsky, S., 69 Kunnen, E. S., 352 Kuo, Z. Y., 11 Kupermintz, H., 271 Kurland, M., 226–228, 239, 241, 246 Kusaka, T., 334 Kwon, P., 65 Kyllonen, P. C., 221

L La Paro, K. M., 265, 281 La Pointe, L. B., 225 LaBar, K.S., 50 Ladd, G. W., 278, 280, 282 Ladd, H. F., 256–257, 266, 269–270, 272–273 LaFreniere, P., 113 Lahey, M., 147

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Page 377

Author Index Laine, R. D., 272 Lamb, C., 349 Lamb, M. E., 356 Lancaster, J., 6 Lang, B., 9 Langrock, A., 107, 113 Lanza, S., 181 Lanzetta, J. T., 343 Largy, P., 311 Larsen, J. T., 351 Lasley, T. J., 268 Laurance, H. E., 61 Lautrey, J., 55 Lavelli, M., 335–337 Lawrence, A. D., 225, 331, 338 Lawrence, B. M., 227 Lawrence, D. A., 61 Lawrence, H., 243 Leaper, C., 181, 184 Learmonth, A. E., 61 Leather, C. V., 237 Lechuga, M. T., 53 Leclaire, T., 312, 316, 318 LeDoux, J. E., 113 Lee, E. Y., 59 Lee, K., 9 Lee, S., 276 Lee, V. E., 193, 267 Lee-Kim, J., 179, 185–186, 188, 190, 192, 197, 207 Lefkovitch, L. P., 61 Lehnung, M., 61 Lehoux, P., 123 Lehtonen, A., 311, 316 Leichtman, M. D., 40 Leigh, E., 238 Lemaire, P., 311 Lemerise, E., 208 Lemery, K. S., 332 Leonard, L., 141–155, 162–165 Leong, C. K., 301, 307, 316 Leplow, B., 61 Leshikar, E., 51, 67 Leslie, A., 8–9 Lester, B. M., 329, 339, 355 Leung, E. H. L., 355 Leuwers, C., 316 Levelt, W., 150 Levin, I., 316 Levine, B., 48 Levy, G. D., 194–195, 197

377

Levy, S. R., 197–198 Lew, A. R., 61 Lewis, M., 329 Lewkowitz, D. J., 13 Li, S. C., 67 Liben, L. S., 176, 190 Liberman, I. Y., 307, 315–316, 318, 320 Liberzon, I., 331 Lickliter, R., 13, 15, 334 Lie, E., 55–57, 70 Lien, J., 345 Lin, K. H., 177 Lindenberger, U., 67 Lindsay, D. S., 47, 65 Linn, R. L., 264, 276 Liotti, G., 96, 119–120, 125–127 Liss, M. B., 194 Little, J. K., 185 Littler, J. E., 225 Liu, H., 316, 318 Lloyd, S., 224 Lobel, T. E., 187 Lobley, K. J., 225 LoBue, V., 27 Locke, T. F., 121 Lockl, K., 227 Loeb, D., 142 Loebell, H., 151 Loewen, E. R., 63 Logie, R. H., 222, 236 Long, J. M., 62 Lopez, N. L., 123 Lorenz, K., 11 Louis-Alexandre, M.-F., 314, 316, 319 Lovibond, P. F., 108, 111 Lowe, L., 184 Lustig, C., 232 Lutkus, A. D., 264 Lyon, G. R., 288 Lyons-Ruth, K., 100 Lyster, S.-A. H., 319 Lytton, H., 181, 184

M Maass, A., 200 Maccoby, E. E., 181 MacDonald, K., 1–2, 7, 16, 20 MacDonald, S., 42, 53 Macfie, J., 121, 128 Macken, W. J., 222

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378 Mactutus, C. F., 60 MacWhinney, B., 300 Maguire, E. A., 49, 60 Mähler, C., 227 Mahony, D., 298, 316–317 Malatesta, C. Z., 348–349 Malcuit, G., 185 Malkin, C. M., 356 Malkova, L., 59 Malus-Abramowitz, M., 313 Mandler, G., 43 Mandler, J. M., 44, 53–54 Mangan, P. A., 61 Manis, F. R., 308 Manke, B., 183 Mann, V., 306, 316–317 Maratin, C., 271 Marchman, V. A., 156, 301 Marcos-Ruiz, R., 53 Marentette, P. F., 25 Margie, N. G., 173–174, 176–177, 183, 197–199, 203 Margolin, G., 99–100, 107 Marian, V., 70 Markowitsch, H. J., 50 Marks I. M., 99, 103, 105, 111, 122, 125 Marks, H. M., 193 Marler, J., 147 Marques, J. M., 173–175, 206 Marshall, S., 202–203 Marston, H. M., 62 Martin, C. L., 185–186, 271 Martin, J., 3 Martin, R. P., 117 Marton, K., 147 Maruff, P., 148 Marvin, R. S., 94 Mashburn, A. J., 260, 270, 285 Masse, L. C., 201 Masten, A.S., 110 Mather, M., 46, 67 Matias, R., 355 Matsumoto, A., 42 Matsumura, L. C., 264, 276 Matsuzawa, T., 329, 334 Matusov, E., 329 Mau, W., 193 Mauer, D., 147 Maughan, A., 105–106, 116, 119 Maughan, B., 255, 267, 272, 288–289

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Author Index Mayes, A. R., 58, 60 Mayes, L. C., 350, 356 Mayseless, O., 121, 128 McAdoo, H. P., 203 McAndrews, M. P., 49 McAuley, E., 226 McBride, D. M., 44 McBride, T., 13 McBride-Chang, C., 307, 314, 316–318 McCartney, R. D., 333 McClay, J., 3 McClelland, J. L., 47 McClelland, J., 155–156 McCutchen, D., 320 McDermott, M., 69 McDonough, L., 53 McDougall, I., 6 McElwain, N. L., 121, 128 McFadyen-Ketchum, S. A., 280 McGlothlin, H., 179, 188, 196–197, 200, 203, 207 McGuigan, F., 69 McHale, S. M., 183, 191 McHugo, G. J., 343 McIntyre, J. S., 63 McKee, R. D., 53 McKenzie, B. E., 61 McKone, E., 55 McKoon, G., 44 McLachlan, D. R., 50, 63–64 McLoyd, V., 177 McNaughton, B. L., 47 Mecklenbrauker, S., 55 Mehdorn, M., 61 Melley, S., 126 Meltzoff, A. N., 61 Mendolsohn, M. J., 194 Mendoza, S. P., 119 Mertens, M., 50 Messinger, D. S., 329, 333–334, 339–340, 342, 344–347, 349, 351–356 Meyer, L. A., 264, 276 Michaels, M., 182 Michel, M., 105, 118 Milbrath, R., 148 Miles, J., 126 Mill, J., 3 Miller, C., 147–148, 151, 163–165 Miller, D. B., 10

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Page 379

Author Index Miller, E. M., 20 Milligan, K., 96, 119–120, 125–127 Milne, B. J., 121, 127 Milner, B., 44 Mineka, S., 26, 94–95, 103, 108, 111–114, 117, 123 Mishkin, M., 48–49, 53, 59, 62 Mitchell, D. B., 55 Mitchell, K. J., 46, 50–51, 67 Mithen, S., 6 Mitsudome, A., 51 Miyake, A., 224, 235–238, 240 Mizuno, Y., 329, 334 Moffitt, T. E., 3, 121, 127 Molitor, A., 355 Monroe, S. M., 109–110 Montague, D. P. F., 350–351 Montgomery, J., 147, 149, 153 Monti, L., 62 Moody, J., 195–196, 204 Moore, D. S., 15 Moore, G. A., 342, 355–356 Moore, J. W., 197 Moore, K., 61 Moore, M. K., 61 Morales, M., 332 Moran, G., 347 Moran, R., 264 Moriarty, V., 271 Morrell, R., 106 Morris, L. W., 63 Morris, P., 351 Morris, R. G., 60, 63 Morrison, D. C., 356 Morrison, F. J., 264, 272, 275, 277–278, 282, 286, 288 Mortimore, P., 255 Morton, J., 70 Moscovitch, D. A., 109, 111–112, 117, 123 Moscovitch, M., 39, 48–49 Moses, L. J., 9 Mosteller, F., 269, 271 Mousty, P., 311 Moyer, D., 352 Moylan, P., 348 Muir, C., 225 Mul, D., 21 Mullen, M. K., 42, 69 Multhaup, K. S., 43

379

Mumme, D. L., 93, 329 Mundy, P. C., 353–354, 356 Murphy, F. C., 331, 338 Murphy, K., 55 Murray, E. A., 62 Murray, L., 335 Murry, V., 177 Muse, A., 314, 316–318 Muthén, B., 279 Myers, C. E., 62 Myers, L. C., 194 Myers, M., 355 Myers, N. A., 57 Myers, S., 184 Myerson, J., 227

N Nadel, L., 39–40, 48–50, 52, 59–62 Nagel, L., 339 Nagell, K., 27 Nagy, W., 299, 301–303, 306–307, 314, 317 Naito, M., 55 Naveh-Benjamin, M., 51, 67 Neisser, U., 40, 42, 70 Nelson, C. A., 13, 51, 55, 57–58 Nelson, D., 184 Nelson, J., 51 Nelson, K., 21, 39, 69 Nelson-Goens, G. C., 333–334, 340, 342–344, 353 Nemanic, S., 62 Nesdale, D., 174, 177, 200 Nesse, R. M., 99, 103, 105, 111, 122, 125 Nesse, R. M., 7, 110, 116–117, 126 Nesselroade, J. R., 350 Nettelbladt, U., 143–144, 146 Newcomb, M. D., 121 Newcombe, N. S., 55–58, 60–62, 64–68, 70–72, 202 Newman, M. A., 194 Newport, E. L., 25 Newton, P., 233 Nguy, L., 199 Nichelli, P., 223 Nicholls, A. P., 222 Nicolson, R., 225, 230 Niemi, J., 311

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Page 380

Author Index

Nimmo-Smith, I., 331, 338 Nishina, A., 199 Niswander, E., 303 Nolde, S. F., 50, 70 Noll, K. R., 143 Nomanbhoy, D. M., 307, 316 Norman, D. A., 222 Norman, K. A., 66 Novak, D. L., 46 Nucci, L. P., 175, 187 Nugent, L. D., 233 Nunes, S. R., 298 Nunes, T., 310, 314, 317, 319, 321 Nussbaum, M. C., 180 Nwokah, E. E., 329, 340 Nye, B., 271

O O’Brien, M., 108, 139 O’Hara, M., 149 O’Kane, G., 48 O’Keefe, J., 40, 49, 52, 59–60 O’Reilly, R. C., 47 Oetting, J., 141 Ogbu, J. U., 203 Öhman, A., 26 Ohman, A., 94–95, 103, 108, 111–114, 117, 123 Okai, T., 334 Okazaki, M., 51 Okin, S. M., 182 Olejnik, S., 309 Oller, D. K., 25, 347 Olson, K. L., 356 Olson, S. L., 123 Olson, S., 6 Olsson, J., 319 Olweus, D., 174, 198 Oostdijk, W., 21 Opotow, S., 175 Ornstein, P. A., 69 Osgood, D. W., 181 Oster, H., 336, 339, 355 Otterman, L. M., 308 Ottinger, W., 65–66, 68, 71 Ou, Y. S., 203 Ouellette, G. P., 316 Ouston, J., 255 Overman, W. H., 59, 61

Owen, A., 143 Oyama, S., 10–11, 15–17 Ozyürek, A., 25

P Pacton, S., 301, 304, 311–312 Pajer, K. A., 356 Palacios, A., 221 Palmer, S. A., 332 Panagiotides, H., 338 Papagno, C., 148 Papp, L. M., 99, 112 Parisi, D., 71 Park, D., 51, 67 Park, K. J., 186 Park, Y., 185–186, 228 Parke, R. D., 277 Parker, J. F., 65 Parker, J., 174, 188, 198, 203 Parkin, A. J., 221 Parkinson, J. K., 62 Parlade, M. V., 356 Parr, L., 329, 339 Pascalis, O., 58 Pascual-Leone, A., 50, 72 Pascual-Leone, J., 240 Patchen, M., 196 Pate, B. J., 61 Patthey-Chavez, G. G., 264, 276 Paylor, R., 60 Payne, C., 265, 281 Payne, J. D., 191 Peacock, K., 228–232, 236 Pearson, D. G., 222 Pellegrini, A. D., 2, 6–7, 15–17, 29 Penza, S., 105, 118 Perfetti, C. A., 305–306 Perie, M., 264 Perlstone, Z., 43 Perner, J., 9, 63 Perris, E. E., 57 Perruchet, P., 55, 301, 304, 312 Perry, D. G., 186 Perry-Jenkins, M., 183, 191 Peterson, C., 42 Peterson, P. E., 271 Petitto, L. A., 25 Petrella, J. N., 282 Petrides, M., 50, 60, 62

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Page 381

Author Index Pettigrew, T. F., 174, 204 Pettit, G. S., 280 Petucci, M., 151, 163–164 Peucker, M. R., 355 Peuster, A., 61 Phan, K. L., 331 Phillips, D. A., 71 Phillips-Grant, K., 43 Phinney, J. S., 197, 201–202 Piaget, J., 205 Pianta, R. C., 255–256, 260, 264–265, 270, 273–274, 277–278, 280–282, 285 Picariello, M. L., 70 Pickering, S. J., 224 Pigliucci, M., 18 Pike, B., 60 Pillemer, D. B., 38, 42, 70 Pinker, S., 7, 24, 162 Pirrie, S., 230, 243 Pisacane, K., 185, 190, 192 Plant, E. A., 184 Platzman, K. A., 329, 339 Plaza, M., 316, 318 Pleydell-Pearce, C. W., 46, 50 Plooij, F., 339–340 Plunkett, K., 71, 155 Poehlmann, K. M., 351 Pohl, J., 61 Polak Toste, C., 332 Polkey, C. E., 62 Pollatsek, A., 303 Pomerleau, A., 185 Porter, D. A., 49 Porter, K., 334 Posner, M. I., 112 Post, R. M., 109 Potts, R., 6 Povinelli, D. J., 8 Powlishta, K. K., 186 Prattos, D., 182 Pressley, M., 256, 263, 267, 276, 284 Price, B. S., 197 Price, J., 105, 117, 120, 126 Prigogine, I., 348 Pring, L., 308 Proos, L. A., 21 Pruett, J. C., 70 Puchalski, C. B., 332 Puester, A., 59 Punamaki, R., 106–107

381

Purdy, P., 194 Putnam, K., 49 Pye, C., 142

Q Quillian, L., 196, 204 Quina-Holland, K., 41 Quinlan, T., 320 Quinn, D. M., 189 Quintana, S. M., 201, 203

R Rabbitt, P. M. A., 239 Radell, P. L., 13 Radke-Yarrow, M., 99 Radvansky, G. A., 225 Rakison, D., 27 Rakowski, S., 148 Ram, N., 347 Ramsey, P. G., 194 Ranganath, C., 50 Ransdell, S., 232 Rapaport, S., 316 Raphael, L., 256, 263, 267 Rapoport, J. L., 51 Rasi, J. A., 107, 116, 122 Ratcliff, R., 44 Raudenbush, S., 272 Rauf, L., 163–164 Ravid, D., 316 Raye, C. L., 46, 50–51, 67 Rayner K., 303–304, 320 Read, C., 157 Rebello, I., 221 Records, N., 139–140 Reddy, V., 351 Redican, W. K., 329, 339 Redmond, S., 142 Reed, J., 203 Reese, E., 69 Reeve, H. K., 16 Reich, J., 333, 351 Reichle, E. D., 305–306 Rekkas, P. V., 49 Repetti, R. L., 123, 129 Resnikoff, D., 121 Restrepo, M. A., 145

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382 Rhen, T., 19 Rice, H. J., 50 Rice, M., 141–143, 146, 164 Richard, A. J., 94, 106 Richardson, L., 142 Richardson, C., 198, 200 Ridgeway, D., 90, 93 Ridley, M., 5 Rimm-Kaufman, S. E., 273, 280 Rinn, W. E., 330 Ritchey, P. N., 195 Rivers, J. C., 267, 275, 285–286 Rivkin, S. G., 257, 270, 273 Roach, M. A., 348 Robbins, T. W., 62 Roberts, C. R., 201 Roberts, N., 60 Roberts, R. E., 177, 201 Roberts, S. S., 143 Roberts, W., 355 Robila, M., 201, 203 Robinson, A. J., 58 Robinson, J. W., 319 Robinson, J., 121 Rochat, P., 337 Roediger, H. L. III, 44 Roeser, R., 181 Rogers, S. J., 332 Rogers, T., 355 Rogosch, F. A., 121, 123 Rolls, E. T., 40, 52 Romero, A. J., 177, 201 Romney, D. M., 181, 184 Roseby, V., 103, 113, 129 Rosenberg, J. S., 7 Ross, S., 356 Roth, S., 48–49 Rothbart, M. K., 112, 332 Rotondo, J. L., 350 Rovee-Collier, C., 52–53, 57, 335 Royer, C., 316 Rubin, D. C., 38, 41, 50, 63 Rubin, H., 301, 314 Rubin, K. H., 174, 188, 198, 203, 356–357 Ruble, D. N., 185 Ruch, W., 340 Ruck, M., 198–200 Rudy, J. W., 60 Ruffman, T., 63 Russell, J. A., 314, 341

Page 382

Author Index Russell, J., 61, 181, 183, 191 Rutherford, M., 9 Rutland, A., 174, 177, 200, 206 Rutter, M., 110, 255, 267, 272, 288–289 Ryan, E. B., 226 Ryan, L., 48–50

S Sabbagh, M. A., 9–10 Sadler-Morris, S., 60 Sagar, H. A., 196 Saito, S., 235–237 Salmon, K., 69 Sameroff, A., 288 Sandberg, E. H., 61 Sanders Thompson, V. L., 202 Sanders, W. L., 267, 275, 285–286 Satlow, E., 61–62 Saults, J. S., 230 Schaafstal, A. M., 225 Schactel, E. G., 38 Schacter, D. L., 39–40, 44, 50, 63–64, 66 Schelleter, C., 142 Schenk, F., 60 Schiefele, U., 181 Schiffman, H., 41 Schlichting, C. D., 18 Schmidt, K. L., 345 Schmidt, L. A., 356–357 Schneider, W., 45, 227 Schnyer, D. M., 48–50 Schofield, J., 196 Schommer, M., 303, 306 Schraagen, J. M. C., 225 Schreiber, P., 157 Schreuder, R., 301, 303, 305 Schuele, C. M., 143 Schugens, M. M., 62 Schuster, B. V., 298 Schütze, C., 142 Schuyler, G., 271 Schwartz, D., 280 Schwartz, R., 147 Schwartzman, A., 123 Schwiebert, C., 320 Scott, J., 303, 306 Sechrist, G., 197 Secrist, C., 342–344, 353 Seeman, T. E., 123, 129

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Author Index Segal, L., 355 Segal, Z. V., 109 Segui, J., 303 Seibert, J. M., 353 Seid, M., 107 Seidenberg, M. S., 156, 308 Selby, S., 299 Seligman, M. E. P., 23, 26, 111 Sénéchal, M., 311–313, 316–318 Senghas, A., 25 Serbin, L. A., 123 Seress, L., 51 Servis, L. J., 191 Shackelford, T. K., 94 Shadish, W. R., 315 Shah, P., 224 Shallice, T., 222 Shanahan, T., 298 Shankland, R. S., 347 Shapiro, A. F., 342–344, 353 Shapka, J. D., 288 Sharpe, H., 50 Shedden, K., 279 Sheeber, L. B., 126 Sheingold, K., 42 Shepard, B., 348–349 Shepard, R. N., 7 Sherman, F., 194 Shiffrin, R. M., 43– 44 Shimamura, A. P., 63 Shin, Y., 185 Shipman, K., 105, 118 Shkolnik, J. L., 271 Shonkoff, J. P., 71 Shouldice, A., 96 Shu, H., 314, 316–318 Siddle, D. A. T., 108, 111 Siedentop, D., 268 Siegel, L. S., 226 Sigman, M., 353 Simcock, G., 70 Simion, F., 333–334, 340 Simons, R. L., 177 Simpson, J. A., 5 Singson, M., 306, 316–317 Sinka, I., 142 Sinno, S., 173–174, 176–177, 183, 191, 197–198, 203 Siong, S. C., 51 Slee, J., 55

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383

Sleeman, F., 148 Sleigh, M. J., 13 Slobin, D., 155 Sloman, L., 96, 105, 117, 119–120, 125–127 Slotnick, S. D., 50 Sluzenski, J., 58, 61–62, 65–68, 71 Smetana, J. G., 175, 179, 203, 205 Smith, A., 255 Smith, E., 139 Smith, L. B., 11, 71, 329 Smith, S. S., 194, 196, 204 Solantaus-Simula, T., 106–107 Sommer, T., 55 Son, S.H., 272, 282 Soussignan, R., 330, 346 Sowell, E. R., 51 Spackova, N., 60, 62 Spangler, G., 125 Spear, N. E., 13 Speltz, M. L., 127 Spencer, M. B., 202–203 Spencer, S. J., 189 Spieker, S., 338 Spiers, H. J., 49 Spiers, H., 66 Spitz, R. A., 334 Squire, L. R., 44, 47, 53, 63 Sroufe, L. A., 95, 128, 186, 328, 334–335, 340 Stallman, A., 303, 306 Stangor, C., 179, 188, 190, 192, 197, 207 Stanny, C. J., 42 Steele, C. M., 189, 200 Steinberg, L., 5, 19 Steiner, J. E., 332 Steinvorth, S., 48 Stengers, I., 348 Stepankova, K., 60, 62 Sterling, C., 302 Stern, E., 124 Stevens, K. I., 107, 116, 122 Stevenson, H. C., 202–203 Stevenson, H. W., 276 Stevenson-Hinde, J., 96 Steyvers, M., 44 Stifter, C. A., 352 Stiles, J., 51 Stipek, D. J., 264, 273–274 Stockley, S., 271 Stoddart, T., 186 Stone, C. A., 305–307

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Page 384

Author Index

Stone, V., 9 Striano, T., 353, 356 Stringer, C., 6 Stringer, S. M., 40, 52 Stuart, G., 233 Stuhlman, M., 265 Sturge-Apple, M. L., 99, 112 Stuss, D. T., 46, 50 Sugden, K., 3 Suomi, S. J., 329, 339 Surbey, M. K., 20 Sussman, A. L., 65 Suzuki, J., 334 Suzuki, W. A., 48 Swanson, H. L., 221, 227 Swanson, L., 154 Swearer, S. M., 198 Sweeney, J. A., 41 Swenson, L. P., 201 Symons, D., 3, 347 Szalacha, L. A., 177 Szatmari, P., 355

T Tabasso, A., 333 Taft, M., 303 Tajfel, H., 177 Takai-Kawakami, K., 334 Takano, K., 51 Takeshita, H., 329, 334 Tarver, S., 201 Tattersall, I., 6 Taylor, A., 3 Taylor, J., 177 Taylor, M., 10, 63 Taylor, R. J., 202 Taylor, S. E., 123, 129 Taylor, S. F., 331 Teasdale, J. D., 109 Tehan, G., 225 Teixeira, R. A., 204 Tellegen, A., 110 Tenney, Y. J., 42 Tereshinski, C. A., 309 Tesak, J. A., 128 Tesman, J. R., 348–349 Teti, L., 105, 118 Tetirick, J. C., 43 Tevendale, H. D., 201

Thaiss, L., 50 Theimer, C. E., 192 Theimer-Schuette, C., 183 Thelen, E. U., 11, 71, 329, 331, 333, 354 Thijs, J., 194 Thirkield, A., 106 Thomas, J. G., 243 Thomas, K. M., 55 Thompson, C., 182 Thompson, D., 61 Thompson, J., 332 Thompson, P. M., 51 Thompson, R.A., 129 Thomson, J., 307 Thomson, N., 223, 225 Thordardottir, E., 142 Thornton, M. C., 202 Thorp, D., 353–354 Tian, Y., 345 Tignor, T., 61 Tobin, M., 51 Toga, A. W., 51 Tomasello, M., 8, 27, 157 Tomblin, J. B., 139–140, 147–148, 165 Tomesen, M., 309 Tomkins, S. S., 328 Tomlinson, W. T., 13 Tomonaga, M., 334 Toms, F. D., 202 Tooby, J., 2–5, 7, 15–16, 28, 94–95, 110 Torgesen, J., 288 Totereau, C., 311 Toth, S. L., 121 Towse, J. N., 221, 227–232, 234–237, 240–244 Trappenberg, T. P., 40, 52 Tredoux, C., 174 Treiman, R., 310 Treisman, A. M., 51 Trevarthen, C., 335 Trinke, S., 121, 128 Trinkler, I., 49, 66 Tronick, E. Z., 342, 347, 349–351, 356 Troop, W., 278 Tropp, L. R., 174, 204 Trouard, T., 49 Trower, P., 96, 119 Tulving, E., 43–44, 46, 48, 50 Turiel, E., 175, 180, 182, 186, 205, 208 Turkewitz, G., 12–13

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Page 385

Author Index Turner, J. C., 177 Turner, M. L., 224, 231 Turner, M., 59 Turner, R. J., 177 Tuvemo, T., 21 Tyler, A., 299, 301–303 Tyler, L., 153

U Uesiliana, K., 42 Ulrich, B. D., 329 Unsworth, N., 233 Urban, J., 186 Usher, J. A., 42 Utsunomiya, H., 51

V Valdes, R., 264, 276 van Beek, Y., 349 van der Lely, H., 143, 146, 149, 164 Van Egeren, L. A., 348 van Hooff, J. A. R. A. M., 329, 339 Vandekerckhove, M. M. P., 50 vandenBerg, H., 128 Vannest, J., 311 Vargha-Khadem, F., 48–49, 53 Vaughan, K., 307, 314, 317 Vazquez, D. M., 123 Vecchi, T., 224 Vecchiotti, S., 273 Vega-Lahr, N., 334 Venezia, M., 353–354 Venezky, R., 304 Verhoeven, L., 305 Verhulst, F. C., 128 Verkuyten, M., 194 Vermeulen, K., 307, 314, 317 Vigdor, J. L., 256–257, 266, 269–270, 272–273 Viise, N. M., 320 Vincent, M. M., 267, 276, 284 Vizueta, N., 55

W Wachsmuth-Schlaefer, T., 108 Waddington, C. H., 124 Wager, T. D., 113, 331 Wagner, R. K., 307

Wagner, R., 314, 316–318 Wainryb, C., 176 Wakefield, J. C., 94, 125 Waldfogel, S., 38, 41 Walker, H., 342, 348–349 Walker, J., 307, 314, 316 Walker, P., 222 Walker-Andrews, A. S., 350–351 Wall, S., 90 Wallace, C. S., 13, 17, 21, 23, 71 Wallace, D. G., 52 Wallace, S. A., 194, 201 Waller, B. M., 329, 339–340 Wallerstein, J., 121 Wang, Q., 42, 69 Wardrop, J. L., 264, 276 Wargo, J. B., 174 Warick, R., 330, 344 Warrington, E. K., 43 Wasser, S. K., 20 Wat, C. P., 307 Waters, E., 90, 95, 328, 334–335, 340 Waters, G. S., 232, 313 Watkins, K. E., 49 Watson, J., 8 Wattenberg, B. J., 182 Webb, S. J., 57 Webster, M., 59 Wechsler, D., 262 Weerth, C. D., 347 Wei, R., 69 Weinberg, K. M., 351 Weinberg, M. K., 342, 351, 356 Weinstein, R., 264 Weiskrantz, L., 43 Weissberg, R. P., 280 Welch-Ross, M. K., 65 Wellman, H. M., 7, 8 Wells, M. C., 121, 128 Welsh, L. M., 267, 276, 284 Wenner, C. J., 5 West, J., 273, 276 West-Eberhard, M. J., 4, 18–19 Wetzler, S. E., 41 Wewerka, S. S., 53 Wexler, K., 141–142, 146, 164 Wheeler, M. A., 46, 50–51, 72 Wheelwright, S., 9 Whishaw, I. Q., 52, 60 White, S. H., 38

385

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386 Whitecross, S. E., 50 Whitehurst, G. J., 271–272 Whiteley, H. E., 222 Wiesner, M., 121, 127 Wigfield, A., 181, 188–189, 193 Wight, E., 223 Wiley, J. G., 60–61, 72 Williams, J. C., 182 Williams, J. M., 109 Williams, P. L., 330, 344 Williams, R. A., 195 Williamson, S., 256–257 Willms, J. D., 269, 271–273 Willows, D. M., 298 Wilson, E. O., 27 Wilson, P., 148 Wimmer, H., 63 Windle, M., 117 Windsor, J., 148 Winocur, G., 49 Winograd, E., 42 Winter, M. A., 99, 105, 112–113, 116, 118, 124 Wippich, W., 55 Wise, S., 342 Wisenbaker, J., 117 Witelson, S. F., 25 Witherington, D. C., 329 Woermann, F. G., 50 Wolf, P. J., 271 Wolff, P. H., 333–334 Wood, C. H., 185 Wood, N. L., 233 Wood, P. K., 233 Woodcock, R. W., 262 Woodin, E. M., 112 Woodin, M. E., 225 Woodruff-Pak, D. S., 62 Worden, M. S., 55 Worthman, C. M., 20–21

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Author Index Worthy, J., 320 Wrangham, R. W., 8 Wu, F., 194 Wu, S., 316 Wunsch, J. P., 340 Wyatt, J. S., 48–49 Wysocki, K., 301–302

X Xu, F., 9

Y Yaghoub-Zadeh, Z., 298 Yale, M. E., 342, 347, 351–352 Yang, Y., 55 Ybarra, V. C., 201, 203 Yik, M. S. M., 341 Yinger, R., 268 Yirmiya, N., 350, 353 Youngblade, L. M., 191 Yu, K. S., 53

Z Zacks, R., 232 Zadunaisky-Ehrlich, S., 162 Zahn-Waxler, C., 93, 99, 110 Zeman, J., 105, 118 Zentall, T. R., 53 Zhang, X., 139, 147, 165 Zhou, A., 307, 316, 318 Zhu, P., 272–273 Zillmann, D., 110 Zins, J. E., 280 Zlochower, A., 345 Zola-Morgan, S., 39, 44, 60 Zwaigenbaum, L., 355

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Page 387

Subject Index

A

anticipatory smiles, referential communication and, 353–354 approach-avoidance behavior interparental conflict and, 100–103 smiling neurophysiology and, 330–331 arousal process children’s reactivity to family conflict and, 110–111 smiling interaction dynamics and, 351 attachment cross-cultural variations in protection of, 102–103 defense interdependency with, 101–103 ethological perspectives on, 94–100 felt-security and, 96–98 attention behaviors, academic achievement and role of, 277–280 atypically developing infants, smiling in, 355–356 auditory localization implicit memory studies and, 57 source memory development and, 71 auditory word learning, children’s development of working memory and, 225–227 autism, theory-of-mind mechanism and, 1–2 autobiographical memory categorization of, 45–47 in early childhood, 53–54 language, cognition and social interactions and, 39–40, 70–71 lifetime distribution of, 41–43 source memory in childhood and, 65–66 automated measurement systems, smile research, 345–346 autonoetic recall, defined, 46–47 auxiliary are, specific language deficits and use of, 150–151

absence of impairment hypothesis, phenotypic plasticity and, 20–22 academic achievement, classroom experience and, 276–280 academic context, gender identity in exclusion in, 188–190 inclusion in, 192–193 action tendencies, in childhood control systems, 96–98 “active empathy” pattern, as response to interparental conflict, 108 active memory codes child development of, 225–227 working memory and, 223–225 adaptive function, in childhood control systems, 96–98 adolescence gender identity and exclusion patterns in, 187–188 race/ethnicity-based friendship segregation and, 195–198 adult working memory, endurance of, 230–232 affect theory, smiling neurophysiology and, 330–331 affiliation attachment and defense system and, 101–103 ethological perspectives on, 96–100 age distribution of memory as function of, 41–43 of student, outcomes assessment in educational research and, 273–274 agonic families, mobilizing/camouflaging patterns in, 119 amnesia explicit memory test in early childhood, 53–54 hippocampal lesions and, 48–49 long-term memory research and, 43–45 amplitude measurements, smiling research, 344 amygdala, children’s reactivity to family conflict and, 113–116 analogy, morphological knowledge and, 300 animal models, place learning studies and, 59–61

B base morphemes morphological representations and access and, 303–304 reading and, 304–309

387

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388

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Subject Index

behavioral ontogeny, developmental systems theory and, 12–14 behavioral outcomes assessment, classroom experiences and, 280–282 binding process childhood amnesia and, 66–68 episodic memory, 50–51 biological adaptations, evolutionary psychology and, 5–7 blind infants, temperament-based studies of smiling in, 332–333 bound morphemes, language structure and, 298–300 brain damage dense amnesia and, 40–41 long-term memory research and, 43–45 source amnesia and, 41 brain function delayed nonmatch to sample tasks and, 58–59 development of, episodic memory and, 51–52 experience as tool for, 71 human memory and role of, 47–52 binding process and, 50–51 frontal lobes and, 50 hippocampus and, 47–49 bullying/victimization, exclusion through, 198–200

C camouflaging-insecure pattern response children’s development of, 126–127 children’s reactivity to family conflict and, 118–119 to interparental conflict, 103–108 card-order experiments, representational overlap and forgetting research and, 235–237 career context for gender identity exclusion and, 188–190 inclusion and, 192–193 caregiving systems children’s development of, 128–129 children’s reactivity to family conflict and, 122–123 defense system and, 107–108 ethological perspectives on, 96–100 gender-based exclusion patterns and, 183–185 smiling interaction dynamics in, 350 arousal modulation and, 351 gazing coordinated with, 351–352

causality, complex span tasks and memory development, 242–244 central executive system, working memory mechanisms and, 221–225 change mechanisms, working memory development and, 239–241 child development ethnic identity and, 201–202 exclusion mechanisms and, 175–177 gender identity and academic and career-based context, 188–190 exclusion behaviors and, 181–190 inclusion mechanisms and, 201–204 interparental conflict and camouflaging response to, 126–127 caregiving response to, 128–129 demobilizing response to, 127–128 dominant response to, 128 emotional insecurity effects, 123–125 emotional insecurity trajectories, 123–130 mobilizing response to, 126 specificity in security patterns regarding, 125–130 National Institute of Child Health and Human Development study, 254–289 age of entry into school issues, 273–274 child outcomes and family characteristics, 262–263 children and family characteristics, 258 classroom experiences as influence on, 275–284 classroom observations and outcome assessments, 256–263 classroom observation system and related issues, 260–262 classroom stability, 266–267 class size issues, 269–270 “design space” in elementary school classrooms, 285–287 differential effects of classroom experiences, 282–284 educational achievement in elementary grades, 276–280 future research issues, 289 grade-level environmental factors, 265–266 influences on outcomes, 270–275 instructional and social environmental factors, 263–267

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Subject Index limitations on schooling, 284–285 participant characteristics, 257–260 public vs. private school environment, 271–273 quality issues in educational opportunity, 287–288 school and teacher characteristics, 258–260 schooling research background and design, 254–256 social/behavioral outcomes in elementary years, 280–282 teacher-based classroom characteristics, 267–270 value of schooling quality, 288–289 race/ethnicity-based friendship segregation and, 195–198 racial socialization theory and, 202–203 smiling, interactive development of amplitude differences in types of smiles, 344 arousal modulation, 351 atypically developing infants, 355 automated measurements of, 345–346 caregiver interactions, 351–352 as continuous action, 343 continuous indices/distinct types rapprochement, 347 continuous positive emotional processes, 343–346 developmental outcomes and, 355–357 distribution of smile types during, 344 Duplay smiles, 342–343 dynamics of, 350 early development studies, 335–337 emergence of, 334–335 eye constriction-Duchenne smiles, 337–339 future research issues, 357 gaze aversion theories, 352 gazing at caregiver and, 351–352 infants’ perceptions of, 350–351 interactive development, 347–351 mouth opening-play smiles, 339–342 neonatal smiling, 333–334 neurophysiological mechanisms, 330–331 pragmatic aspects of, 354–357 quantity and quality analysis, 337–347 rating studies, 344–345 referential communication and, 353–354 representativeness of, 354–355

Page 389

389

social smiling development, 348–350 temperament-based studies, blind and sighted infants, 332–333 theoretical orientation, 328–330 social inclusion/exclusion and, 173–175 stable parent-child relationships and, 129–130 working memory systems and basic mechanisms of, 219–221 basic principles, 225–227 endurance of working memory, 230–232 integration of theories on, 241–244 micro-task-switching and memory performance, 234–235 models for, 239–241 qualitative analysis of, 246 representational overlap and forgetting research, 236–237 childhood amnesia, 38–39 binding and, 66–68 biological bases for lifting of, 62–68 brain maturation and, 40, 51–52 characteristics of, 40–43 implicit memory studies and role of, 57 source memory and, 63–66 children’s reactivity to conflict caregiving pattern in, 122–123 demobilization pattern and, 119–120 domains of reactivity, 113–116 dominant pattern in, 120–122 ethological similarities in, 100–103 family origins and patterns in, 108–123 history of interparental conflict and, 109–111 individual differences in, family roots of, 116–123 mobilizing and camouflaging pattern, 118–119 pattern-based approach to, in interparental relationship, 103–108 stable parent-child relationships, 117–118 Chinese, morphological knowledge and reading skills development in, 306–309 chronometry of recall, working memory research and, 233 classroom observation techniques academic achievement and classroom experience analysis, 276–280 class size assessments, 269–270 “design space” analysis, 285–287

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390

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Page 390

Subject Index

developmental assessment based on, 275–284 differential effects analysis, 282–284 educational policies and classroom environments, 270–275 grade-level analysis, 265–266 instructional quality and social environment assessment, 263–267 limitations of, 284–285 outcome assessments and, 256–263 social/behavioral assessment of elementary students, 280–282 stability of classroom experience assessed with, 266–267 teacher characteristics and, 267–270 class size impact on teachers of, 270–273 outcomes assessment and effects of, 269–270 cognitive-contextual framework, children’s reactivity to family conflict and, 114–116 cognitive domain theory gender-based exclusion patterns and, 183–185 working memory development and, 241–244 cognitive mechanisms ability variations and working memory development, 240–241 child development and activation of, 124–125 evolved probabilistic cognitive mechanisms, 22–24 exclusion based on, 176–177 memory development and, 39–40 modularity of, 7–10 monomorphic structure, 2–3 selective attention and, 26–27 smiling development and, 328–330 species-universal mechanisms, 4–5 working memory and, 219–220, 224–225 color constancy mechanisms, biological adaptation of, 7 color context memory binding and, 68 visual-paired-comparison (VPC) task and, 58 combination, morphological knowledge and, 300 communities, as exclusion mechanisms, 199–200 competence beliefs, academic and careerbased gender identity and, 188–190

completion time measuremenets, complex count span research and, 227–228 complex span tasks componential analysis of, 237–239 variations in working memory model and effectiveness of, 242–244 working memory and, 224–225 complex stimuli, memory binding and, 67–68 comprehension skills, processing deficits and limitations on, 149–151 computational models, processing limitations and specific language impairment, 158 “concerned” response pattern, to interparental conflict, 108 conditional adaptations, phenotypic plasticity and, 19–22 conditioning theory, children’s reactivity to family conflict and, 109–111 conjugate reinforcement paradigm early childhood memory and, 52–54 implicit memory studies and, 57 constrained developmental systems, evolved probabilistic cognitive mechanism, 25–26 continuous action, smiling as, 343 discrete actions and, 347 contradictory behavior, interparental conflict and, 100–103 counting span task children’s development of working memory and, 226–227 endurance of adult working memory and, 230–232 research design for, 227–239 cross-gendered activities, gender-based exclusion and, 181–190 crosslinguistic differences in morphological knowledge, 298 in specific language impairment, 145–146 spelling skills and phonological transparency and, 311–312 cross-race friendships, inclusion based on, 202–203 cued conditioning studies, stimulus characteristics of interparental conflict and, 111–113 cued recall, source memory in childhood and, 66 cultural differences episodic memory development and, 69–71 smiling development and, 334–335

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Subject Index

D declarative memory, defined, 44 decomposition hypothesis, morphological representations and access and, 303–304 defense system attachment interdependency with, 101–103 caregiving system and, 107–108 child development and activation of, 123–125 dominance strategy in, 120–122 emotional security theory and, 96–100 interparental conflict and, 100–103 pattern-based responses for maintenance of, 103–108 deferred imitation, for explicit memory in early childhood, 53–54 degree of use comparisons, specific language impairment and, 160–164 delayed nonmatch to sample (DNMS) task, infantile amnesia and, 58–59 demobilizing-insecure pattern children’s development of, 127–128 children’s reactivity to family conflict and, 119–120 as response to interparental relationship, 106–108 dense amnesia, childhood amnesia and, 40–41 derivational morphemes language structure and, 299–300 morphological representations and access and, 303–304 reading and, 304–309 spelling skills and, 310–313 determined epigenesis, developmental systems theory and, 10–12 developmental amnesia, hippocampus and, 48–49 developmental heterochronicity, neonatal smiling and, 333–334 developmental outcomes, infant smiling and, 355–357 developmental psychology evolutionary psychology and, 1–2 paradigms of, 28–29 developmental science. See child development; educational research developmental systems theory basic principles, 10–14 evolutionary psychology and, 2

Page 391

391

genetic determinism and, 15–18 “instinctive” behavior and, 11–12 phenotypic plasticity and, 18–22 probabilistic epigenesis, 10–11, 14–15 timing, experience and species-typical behavioral ontogeny, 12–14 developmental timing evolved probabilistic cognitive mechanisms and, 25 species-specific behavioral ontology, 12–14 development of theory of mind model, modularity and, 7–10 differential effects analysis, classroom experiences and educational outcomes, 282–284 discrimination behavioral mechanisms for, 177 in infant smiling, 354–357 distal landmarks, place learning studies and, 60–61 distribution of smiles, social interaction and, 344 domain-general mechanisms, theory-of-mind mechanism and, 9 domestic violence children’s response to, 100 emotional security theory and, 88 mobilizing/camouflaging patterns in response to, 119 dominant-insecure pattern children’s development of, 128 children’s reactivity to family conflict through, 120–122 ethological perspectives on, 96–100 felt-security and, 102–103 as response to interparental conflict, 107–108 dominant-secure pattern, as response to interparental conflict, 106–108 Duchenne smiles, characteristics of, 337–339 Dutch processing limitations in SLI and, 158–160 specific language impairment in, 143–144 dynamic systems theory, smiling development and, 328–330 neonatal smiling and, 334 social smiling emergence, 335–337 dyslexic students, morphological knowledge and reading skills in, 307–308

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392

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Page 392

Subject Index

E ecological consequences, mobilizing/camouflaging response to family conflict and, 119 educational research instructional quality and social environment, 263–267 morphological analysis and, 300–302 National Institute of Child Health and Human Development study, 254–289 age of entry into school issues, 273–274 child outcomes and family characteristics, 262–263 children and family characteristics, 258 classroom experiences as influence on, 275–284 classroom observations and outcome assessments, 256–263 classroom observation system and related issues, 260–262 classroom stability, 266–267 class size issues, 269–270 “design space” in elementary school classrooms, 285–287 differential effects of classroom experiences, 282–284 educational achievement in elementary grades, 276–280 future research issues, 289 grade-level environmental factors, 265–266 influences on outcomes, 270–275 instructional and social environmental factors, 263–267 limitations on schooling, 284–285 participant characteristics, 257–260 public vs. private school environment, 271–273 quality issues in educational opportunity, 287–288 school and teacher characteristics, 258–260 schooling research background and design, 254–256 social/behavioral outcomes in elementary years, 280–282 teacher-based classroom characteristics, 267–270 value of schooling quality, 288–289

egalitarian-based family structure, inclusion patterns and, 190–191 embedded-process model of working memory, 242–244 emotional intensity hypothesis, rating studies of smiles, 344–345 emotional overinvolvement, as response to interparental conflict, 107–108 emotional security theory children’s developmental trajectory and, 123–130 development of, 88–89 differences in types of security, 96–100 family origins as correlates of, 108–123 functionalist contexts in, 91–93 functionalist goal in, 90–91 future research issues, 130–131 interparental conflict and parent-child subsystem distinctions in, 94–108 pattern-based approach to interparental relationship, 103–108 principles, processes, and pathways in, 90–94 prior translations of functionalist perspective, 93–94 role of ethology in, 95–96 similarities in types of security, 100–103 emotion theory. See also smiling, interactive development of autobiographical memory and, 47 enclosed avoidance, children’s development of, 126–127 English specific language impairment in, 141–142 tense-agreement morphemes with SLI in, 158–160 environmental factors biological adaptations and, 5–7 temperament-based studies of smiling in blind and sighted infants and, 332–333 epigenesis developmental systems theory and, 10–12 “instinctive” behavior and, 11–12 episodic buffer, working memory mechanisms and, 222–225 episodic memory alternative developmental theories of, 69–72 autobiographical memory and, 45–47 binding process, 50–51, 66–68 brain area development and, 51–52 in early childhood, 53–54

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Subject Index frontal lobe function and, 50 hippocampus and, 47–49 qualitative vs. quantitative change in development of, 71–72 source memory in childhood and, 66 ethnic identity. See race/ethnicity identity ethological theory child development and interparental conflict and, 123–130 differences in types of security and, 96–100 emotional security theory and, 88–89 family origins and emotional security correlates, 108–123 future research issues, 130–131 pattern-based emotional security and interparental conflict, 103–108 relations between types of security and, 95–96 security differences in interparental conflict and parent-child subsystems and, 94–108 evolutionary psychology basic principles, 3–10 biological adaptations, 5–7 children’s reactivity to family conflict and, 114–116 current trends in, 1–2 demobilizing response to family conflict and, 119–120 dominance response to family conflict and, 121–122 mobilizing/camouflaging patterns and, 118–119 modularity and, 7–10 paradigms of, 28–29 phenotypic plasticity and, 18–22 sensitization to interparental conflict and, 112–113 smiling development and, 334–335 species-universal characteristics, 4–5 summary of assumptions concerning, 14–15 supportive family systems and, 117–118 evolved cognitive mechanisms evolutionary psychology and, 2, 4, 14 genetic determinism and, 15–18 modularity of, 7–10 phenotypic variation and, 18–22 probabilistic epigenesis vs., 15–22 evolved probabilistic cognitive mechanisms evolution of, 22–24

Page 393

393

language development and, 24–26 prepared learning, 26–27 exclusion academic and career-based gender identity as basis for, 188–190 bullying/victimization and, 198–200 children’s experiences with, research overview, 173–175 definitions, 175–180 family environment and, 182–185, 195 friendship segregation and, 195–198 future research issues and, 204–209 gender as basis for, 181–190 peer interactions and patterns in, 185–188, 196–200 race/ethnicity as basis for, 194–200 schools/communities as mechanisms for, 199–200 executive function age-related working memory development and, 239–241 theory-of-mind mechanism and, 9 working memory mechanisms and, 221–225 experience developmental systems theory and, 12–14 implicit memory studies and role of, 56–57 species-specific behavioral ontology, 12–14 explicit memory classification, 44–45 development of, 39–40 in early childhood, 52–54 implicit memory and absence of, 55–57 visual-paired-comparison (VPC) task and, 58 exploratory system attachment and defense system and, 101–103 ethological perspectives on, 96–100 extraexperimental errors, source memory and childhood amnesia and, 63–66 eye-constriction, as smiling mechanism automated measurement systems for, 345–346 Duchenne smiles, 337–339 Duplay smiles, 342–343 interactive development of, 348–350 open-mouth smiles, 340–342 eye-direction detector, evolutionary psychology and, 8–10

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394

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Page 394

Subject Index

F facial-feedback hypothesis, smiling neurophysiology and, 330–331 family conflict theory caregiving pattern and, 122–123 children’s reactivity to interparental conflict, 109–111, 113–116 correlates of emotional security and, 108–123 demobilizing pattern and, 119–120 dominant pattern and, 120–122 individual differences in security patterns, 116–123 mobilizing and camouflaging patterns and, 118–119 security systems and, 117–118 selectivity in sensitization to conflict, 111–113 family environment academic achievement and role of, 277–280 educational research and role of children’s outcomes based on, 262–263 outcomes assessment and, 258 gender identity and exclusion patterns and, 182–185 inclusion patterns and, 190–191 race/ethnicity issues in exclusion and, 195 inclusion and, 202–203 fear stimuli, children’s reactivity to family conflict and, 113–116 feature binding, autobiographical memory and, 46–47 felt-security in childhood control systems, 96–100 children’s development of, 129–130 emotional, cognitive and neurobiological regulation mechanisms, 100–103 environmental variations across cultures, 102–103 interparental conflict and, 101–103 fitness values, phenotypic variation and, 3 fixed window processing model, complex span tasks and, 237–239 “foreseeing” organisms, phenotypic plasticity and, 21–22 forgetting endurance of working memory and variables in, 232

future research issues, 245–246 infantile vs. childhood amnesia and, 42–43 processing content as factor in, 240 representational overlap and nature of, 235–237 free morphemes, language structure and, 298–300 free recall, source memory in childhood and, 66 frequency of words, morphological knowledge and reading skills development and, 304–309 friendship cross-race friendships, 203–204 race/ethnicity-based exclusion patterns and segregation of, 195–198 frontal lobes delayed nonmatch to sample tasks and, 58–59 episodic and semantic memory and, 50 source memory errors and lesions in, 63–66 full-listing hypothesis, morphological representations and access and, 303–304 functionalist perspective, emotional security theory and, 95 function word deficits, in Romance language impairment disorders, 145

G galvanic skin responses (GSR), implicit memory studies and, 56–57 gazing aversion and smiling mechanism, 352 smiling coordinated with, 351–352 gender identity academic context and exclusion based on, 188–190 inclusion based on, 192–193 career expections and, 188–190 exclusion based on, 175–179 in family structure exclusion and, 182–185 inclusion and, 190–191 future exclusion/inclusion research issues and, 206–209 peer interactions and exclusion, 185–188 inclusion, 191–192 prevalence of, in exclusion research, 180 social exclusion based on, 181–190

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Page 395

Subject Index genetics developmental meaning in, 11 of specific language impairment, 140 unrealistic plasticity and, 15–18 gene X environment interactions evolutionary psychology, 4 genetic determinism and, 17–18 phenotypic plasticity and, 19–22 gene X environment X development interactions evolved probabilistic cognitive mechanisms, 22–24 language development and, 26 prepared learning and, 27 German processing limitations in SLI and, 158–160 specific language impairment in, 143–144 global model of working memory, complex span tasks and, 242–244 goal-directed control systems children’s use of, 96–98 felt-security and, 102–103 grammatical morpheme use degree of use comparisons, 161–164 English-language impairment and, 141–143 processing limitations and, 156–158 specific language impairment and deficits in, 152–156 group membership, exclusion/inclusion research and, 205–209

H “hard-wired” traits epigenesis and, 11–12 genetic determinism and, 17–18 Hebrew language, degree of use comparisons in SLI and, 162–164 hippocampus amnesia and lesions in, 48 delayed nonmatch to sample tasks and, 59 developmental amnesia and, 48–49 development of, 51–52 episodic and semantic memory and role of, 47–49 infantile amnesia and development of, 54, 62 place learning and role of, 60–61 role of experience in development of, 71 spatial tasks and role of, 61–62 human evolution, biological adaptations and, 5–7

395

human memory system. See also working memory model architecture of, 43–47 brain bases of, 47–52 place learning studies and, 60–61 hypoxia, semantic memory development and, 48–49

I imaging studies frontal lobe function and episodic and semantic memory, 50 hippocampus, adult memory research and, 49 smiling neurophysiology and, 330–331 implicit memory absence of explicit memory and, 55–57 classification, 44–45 development of, 39–40 imprinting epigenesis and, 12 genetic determinism and, 17–18 inclusion academic/career contexts for, 192–193 children’s experiences with, research overview, 173–175 cross-race friendships and, 203–204 definitions, 175–180 family structure and patterns of, 190–191 future research issues and, 204–209 gender as basis for, 181–193 peer-based contexts for, 191–192 race/ethnicity as basis for, 194, 201–204 racial socializaiton theory and, 202–203 independent seat-work instructional technique, grade-level analysis of, 265–266 individual differences, working memory theories and, 244 infantile amnesia, 38–39 biological bases for lifting of, 58–62 brain development and, 51–52 characteristics of, 40–43 context and visual-paired-comparison tasks and, 58 delayed nonmatch to sample response, 58–59 implicit memory and, 39–40 place learning, 59–61 self-awareness and end of, 70 spatial tasks and, 61–62

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396

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Page 396

Subject Index

infant perceptions, interactive smiling and, 350–351 inflectional morphemes, language structure and, 298–300 information-processing mechanisms evolutionary psychology and, 2 modularity of, 7–10 working memory and age-related memory development, 239–241 integrated memory theories on, 242–244 representational overlap and forgetting research, 236–237 task-switching process and, 228–239 insecure-caregiving pattern, as response to interparental conflict, 107–108 “instinctive” behavior, developmental systems theory, 11–12 instructional quality educational outcomes assessment and, 263–267 grade-level analysis, 265–266 “insulating vacuum flask” metaphor, working memory research and, 228–229 integrated working memory development theories, child development and, 241–244 intentionality detector, evolutionary psychology and, 8–10 interactive smiling development of, 348–350 research overview, 347–348 intergroup research, on exclusion, 175–177 interitem associations, episodic memory and, 50–51 interparental conflict children’s reactivity to, 109–111, 113–116 differences in security categories and, 96–100 emotional security theory and, 89 ethological theory on security characteristics, 95–96 family origins and, 108–123 parent-child attachment system and, 100–103 pattern-based approach to, 103–108 security issues in, 94–108 similarities in security categories in, 100–103 social defense and felt-security in, 98–100 statistics on, 88 stimulus characteristics of, 111–113

intervention studies morphological awareness and, 319–320 morphological knowledge and reading skills, 308–309 intraitem associations, episodic memory and, 50–51 intraspecies stimuli, sensitization to interparental conflict and, 111–113 Italian impairment disorders in, 144–145 processing limitations in SLI and, 160

J joy, social interactions and function of, 328–330 smiling neurophysiology and, 330–331 justification categories for exclusion, 177–179 gender-based exclusion patterns and, 183–185

L language development. See also specific language impairment (SLI) autobiographical memory and, 70 constrained developmental systems, 25–26 evolved probabilistic cognitive mechanisms and, 24–26 morphological awareness and intervention studies, 319–320 phonological awarness and, 319 reading and, 315–317 spelling and, 317–318 vocabulary skills and, 318–319 morphological structure, 298–300 specific language impairment and deficits in, 148–151 timing of, 25 working memory and, 224–225 learning theory children’s reactivity to family conflict and, 109–111 environmental variations and working memory development, 240–241 instructional quality and social environment and, 263–267 limbic-hypothalamic-pituitary-adrenocortical (LHPA) system, children’s development of, insecurity’s effects on, 124–125

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Subject Index linguistic theory morphological awareness and, 313–320 intervention studies, 319–320 phonological awarness and, 319 reading and, 315–317 spelling and, 317–318 vocabulary skills and, 318–319 specific language impairment research and, 146–147 listening span tasks, working memory and, 224–225 list-wise memory searches, recall chronometry and, 233 literacy skills, morphological awareness and, 313–320 long-term memory, typology of, 43–45

M mean length of utterance (MLU) degree of use comparisons, 162–164 English-language impairment and, 141–143 language deficits and use of, 150–151 in Romance language impairment disorders, 145 meliorism, development of, 2 memory. See also working memory model development of, 38–39 in early life, 52–54 menarche, phenotypic plasticity and, 20–22 mental arithmetic adult working memory and, 227–228 working memory mechanisms and, 219–220 mental time travel, episodic memory as, 46–47 micro-task switching integrated working memory theories and, 243–244 working memory performance and, 234–235 “mindreading,” modularity and, 8–10 mobilizing-insecure pattern, as response to interparental conflict, 103–108 mobilizing strategies children’s development of, insecurity’s effects on, 126 children’s reactivity to family conflict and, 118–119 as response to interparental conflict, 103–108 modality-specific representations children’s development of working memory and, 226–227

Page 397

397

multicomponent working memory model and, 242–244 working memory and, 223–225 modularity evolutionary psychology and, 7–10 soft modularity, 23–24 monomorphic structure of cognitive adaptations, 2–3 theory-of-mind mechanism and, 9 moral reasoninig, gender and race/ethnicity exclusion decisions and, 207–209 morphemes, language structure and, 298–309. See also specific morphemes morphological awareness, 313–320 intervention studies, 319–320 phonological awarness and, 319 reading and, 315–317 spelling and, 317–318 vocabulary skills and, 318–319 morphological knowledge analysis and, 300–302 background on, 297–298 degree of use comparisons in SLI and, 161–164, 163–164 future research issues, 320–321 language structure, 298–300 learning processes, 300–304 reading and, 304–309 difficulties and disabilities, 307–308 intervention studies, 308–309 representations and access, 303–304 spelling and, 309–313 information processing, 310–311 phonological transparency, 311–312 strategies for, 312–313 types of, 302–303 morphosyntax English-language impairment and, 143 linguistic theory concerning, 147 processing deficits and limitations on, 149–151 specific language impairment and, 140 vocabulary deficits and, 148–151 Morris water maze, place learning studies and, 60–61 multicomponent working memory model children’s development of working memory and, 226–227 development of, 224–225 modality-specific representations and, 242–244

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Page 398

Subject Index

multicultural research on exclusion, 175–176 gender-based exclusion and, 180

N narrative structure, episodic memory development and, 69–71 National Institute of Child Health and Human Development (NICHD), SECCYD study on child development, 254–289 age of entry into school issues, 273–274 child outcomes and family characteristics, 262–263 children and family characteristics, 258 classroom experiences as influence on, 275–284 classroom observations and outcome assessments, 256–263 classroom observation system and related issues, 260–262 classroom stability, 266–267 class size issues, 269–270 “design space” in elementary school classrooms, 285–287 differential effects of classroom experiences, 282–284 educational achievement in elementary grades, 276–280 future research issues, 289 grade-level environmental factors, 265–266 influences on outcomes, 270–275 instructional and social environmental factors, 263–267 limitations on schooling, 284–285 overview, 254–255 participant characteristics, 257–260 public vs. private school environment, 271–273 quality issues in educational opportunity, 287–288 school and teacher characteristics, 258–260 schooling research background and design, 254–256 social/behavioral outcomes in elementary years, 280–282 teacher-based classroom characteristics, 267–270 value of schooling quality, 288–289

natural selection biological adaptations and, 5–7 evolved probabilistic cognitive mechanisms, 23–24 species-universal mechanisms and, 5 neonatal smiling, interactive development of, 333–334 neural circuits, phenotypic plasticity, 18–22 neural Darwinism, species-specific behavioral ontology, 12–14 neurobiological mechanisms child development and family conflict and, 124–125 children’s reactivity to family conflict and, 110–111, 113–116 smiling development and, 330–331 neuronal circuitry, epigenesis and, 12 neurotransmitter function, children’s development of, insecurity’s effects on, 124–125 nonspecific language impairment (NLI), future research issues, 165–166

O object selection, complex span tasks in working memory research and, 237–239 open-mouth smiles characteristics of, 339–342 eye constriction and, 342–343 interactive development of, 348–350 optionality construct degree of use comparisons in SLI and, 160–164 specific language impairment research, 146–147 orthographic structure morphological knowledge and reading skills development and, 303–309 spelling and morphological knowledge and, 309–313 outcomes assessment in educational research academic achievement and classroom experiences and, 276–280 age of student at school entry and, 273–274 classroom experiences’ developmental impact and, 275–284 classroom observation techniques, 256–263 class size effects, 269–270

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Subject Index cultural valuation of schooling and, 288–289 “design space” analysis and, 285–287 differential effects of classroom experiences and, 282–284 educational policies’ impact on, 270–275 family environment and children’s characteristics, 258, 262–263 future research issues in, 289 grade-level analysis, 265–266 instructional quality and social environment, 263–267 limitations of studies on, 284–285 qualitative analysis of opportunity, 287–288 school environment observations, 260–262 social/behavioral outcomes and classroom experiences, 280–282 stability of classroom experience and, 266–267 teacher characteristics, 258–260 classroom experiences linked to, 267–270

P paradigm building deficits, grammatical morpheme difficulties and, 152–156 parental behaviors academic achievement and role of, 277–280 children’s development of, 128–129 gender-based exclusion patterns and, 182–185 social smiling emergence and, 335–337 temperament-based studies of smiling in blind and sighted infants and, 332–333 parent-child subsystems differences in security categories and, 96–100 ethological theory on security characteristics, 95–96 interparental conflict and, 100–103 pattern-based approach to interparental conflict and, 103–108 security characteristics in, 94–108, 117–118 similarities in security categories in, 100–103 passive memory codes children’s development of working memory and, 225–227 working memory and, 223–225 peer interactions bullying/victimization and, 198–200 cross-race friendships and, 203–204

Page 399

399

exclusion and, 175–176 friendship segregation and, 195–198 gender identity and exclusion patterns and, 185–188, 207–209 inclusion and, 191–192 race/ethnicity-based exclusion patterns and, 195–200 perceptual development developmental timing of, 13–14 interactive smiling and, 350–351 perceptual priming, implicit memory studies, 55 persistence of memory representations, taskswitching process and, 228–229 phenotypic variation cognitive adaptations and, 3 evolved cognitive mechanisms and, 18–22 phonological structure children’s development of working memory and, 225–227 grammatical morpheme difficulties and, 155–156 morphological awareness and, 313–317, 319 morphological knowledge and reading skills development and, 306–309 spelling skills and transparency in, 311–312 working memory mechanisms and, 221–225 place learning, infantile amnesia and, 59–61 plasticity phenotypic, 18–22 unrealistic, 15–18 play activities future research on, 205–209 gender-based exclusion patterns and, 183–185 peer-based inclusion and, 191–192 play smiles, characteristics of, 339–342 polyallelic variation, fitness values and, 3 polymorphic structure, cognitive adaptations, 2–3 predictive validity, of infant smiling, 354–357 preformationism developmental systems theory and, 11 genetic determinism and, 15–18 prefrontal cortex development of, 51–52 episodic and semantic memory and, 50 infantile amnesia and development of, 54 role of experience in development of, 71 prenatal development, species-specific behavioral ontology, 12–14

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400

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Page 400

Subject Index

prepared learning children’s reactivity to family conflict and, 110–111 evolved probabilistic cognitive mechanisms and, 26–27 prespecification, phenotypic plasticity and, 21–22 private school environment, outcomes assessment in, 270–273 probabilistic epigenesis developmental systems theory, 10–11, 14–15 evolutionary psychology and, 2 evolved cognitive mechanisms vs., 15–22 procedural memory, defined, 44 processing mechanisms children’s reactivity to family conflict and, 115–116 specific language impairment and correlates for, 156–158 cross-language impairment comparisons, 158–160 degree of use comparisons in, 160–164 future research on, 166 grammatical morpheme difficulties and, 152–156 overview, 147–164 working memory and age-related memory development and, 239–241 children’s development of, 226–227 complex span task models and, 238–239 efficiency of, 241–244 overview, 224–225 representational overlap and forgetting research and, 235–237 task-switching working memory research and, 227–230 time-based resource-sharing model of working memory and, 233–235 “processing plus memory” episodes, working memory research and, 229–230 prosopagnosia, implicit memory and, 55–57 proximity-seeking behavior, emotional security theory and, 94–95 psychological mechanisms, working memory theories and, 244 psychopathology, children’s development of, insecurity’s effects on, 123–130 psychosocial stress, phenotypic plasticity and, 20

public school environment, outcomes assessment in, 270–273

Q qualitative analysis educational opportunity, 287–288 episodic memory development and, 71–72 social smiling emergence and, 337–347 quantitative analysis episodic memory development and, 71–72 social smiling emergence and, 337–347

R race/ethnicity identity bullying/victimization and, 198–200 cross-race friendships and, 203–204 exclusion based on, 175–179, 194–200 family-based exclusion and, 195 friendship segregation and, 195–198 future research issues and, 208–209 inclusion based on, 201–204 peer-based exclusion and, 195–200 schools/communities as exclusion mechanisms for, 199–200 racial socialization theory, family context for, 202–203 rating studies, of smiles, 344–345 reading skills morphological awareness and, 315–317 morphological knowledge and, 304–309 difficulties and disabilities, 307–308 intervention studies, 308–309 research on, 297–298 reading span tasks endurance of adult working memory and, 230–232 representational overlap and forgetting research and, 236–237 working memory and, 224–225 reality monitoring, source memory and, 65–66 recall chronometry integrated working memory theories and, 243–244 representational overlap and forgetting research and, 237 working memory research and, 233

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Subject Index referential communication, smiling and, 353–354 regulation of neural circuits, evolutionary psychology and, 4 rehearsal, working memory performance and role of, 235 representational overlap, working memory and, 235–237 representativeness, infant smiling and, 354–355 research design issues in developmental science, 254–256 resource-sharing perspectives, representational overlap and forgetting research and, 236–237 “reverted escape” strategy, children’s reactivity to family conflict and, 122–123 role reversal strategies children as caregivers in family conflict environment, 122–123 children’s development of, 128–129 Romance languages, impairment disorders in, 144–145 rote memorization, morphological knowledge and, 300

S same-race peer preferences, exclusion based on, 195–198 sandbox paradigm, place learning studies and, 60–62 scholastic achievement, working memory development and, 226–227 school-age children, working memory development in, 226–227 school environment. See also classroom observation techniques classroom observation and assessment of, 260–262 cross-race friendships in, 203–204 exclusion mechanisms in, 199–200 outcomes assessment in educational research and, 258–260 security patterns caregiving pattern in, 122–123 children’s development of, 125–130 demobilization pattern and, 119–120 dominant pattern in, 120–122 ethological similarities in, 100–103 family origins and patterns in, 108–123

Page 401

401

individual differences in, family roots of, 116–123 mobilizing and camouflaging pattern, 118–119 pattern-based approach to, in interparental relationship, 103–108 stable parent-child relationships, 117–118 selective association model, children’s reactivity to family conflict and, 110–111 selective attention, prepared learning and, 26–27 self awareness academic achievement and regulation of, 278–280 academic and career-based gender identity and, 188–190 autobiographical memory and, 47 episodic memory development and, 69–71 infantile amnesia and, 72 semantic memory autobiographical memory and, 46–47 binding process and, 66–68 development of, 39–40 in early childhood, 53–54 frontal lobe function and, 50 hippocampus and, 47–49 sensitization hypothesis children’s reactivity to family conflict and, 109–111 family conflict and, 108–109 stimulus characteristics of interparental conflict, 111–113 shared-attention mechanism, evolutionary psychology and, 8–10 short-term memory (STM) complex span task models of, 238–239 linguistic skills and, 224–225 phonological loop and, 222–225 recall chronometry and, 233 sighted infants, temperament-based studies of smiling in, 332–333 similarity-based interference, representational overlap and forgetting research and, 237 situation-symptom congruence hypothesis, child’s development of demobilizing insecurity and, 127–128 slave model integrated working memory theories and, 243–244 of working memory mechanisms, 223–225

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Subject Index

smiling, interactive development of amplitude differences in types of smiles, 344 arousal modulation, 351 atypically developing infants, 355 automated measurements of, 345–346 caregiver interactions, 351–352 as continuous action, 343 continuous indices/distinct types rapprochement, 347 continuous positive emotional processes, 343–346 developmental outcomes and, 355–357 distribution of smile types during, 344 Duplay smiles, 342–343 dynamics of, 350 early development studies, 335–337 emergence of, 334–335 eye constriction-Duchenne smiles, 337–339 future research issues, 357 gaze aversion theories, 352 gazing at caregiver and, 351–352 infants’ perceptions of, 350–351 interactive development, 347–351 mouth opening-play smiles, 339–342 neonatal smiling, 333–334 neurophysiological mechanisms, 330–331 pragmatic aspects of, 354–357 quantity and quality analysis, 337–347 rating studies, 344–345 referential communication and, 353–354 representativeness of, 354–355 social smiling development, 348–350 temperament-based studies, blind and sighted infants, 332–333 theoretical orientation, 328–330 social-cognitive mechanisms gender and race/ethnicity exclusion decisions and, 207–209 sensitization to interparental conflict and, 112–113 social Darwinism, evolutionary psychology as, 2 social defense mechanisms children’s reactivity to interparental conflict and, 113–116 demobilizing strategy, 119–120 dominant strategy, 120–122 ethological perspectives on, 96–100 individual differences in, family roots of, 116–123 mobilizing/camouflaging strategies, 118–119

putative and developmental conditions for, 103–105 in secure parent-child relationships, 117–118 social domain theory bullying/victimization and, 198–200 exclusion and, 175–176 friendship segregation and, 195–198 peer-based inclusion and, 191–192 social interactions. See also exclusion; inclusion; peer interactions child development and, 204–209 classroom experiences and, 280–282 educational outcomes assessment and environment for, 263–267 episodic memory development and, 69–71 future research on, 204–209 gender-based exclusion and, 181–190 inclusion and exclusion in, 173–175 peer identity and exclusion patterns in, 185–188 race/ethnicity-based inclusion and, 202–203 race/ethnicity exclusion based on, 194–200 smiling development and amplitude differences in types of smiles, 344 arousal modulation, 351 atypically developing infants, 355 automated measurements of, 345–346 caregiver interactions, 351–352 as continuous action, 343 continuous indices/distinct types rapprochement, 347 continuous positive emotional processes, 343–346 developmental outcomes and, 355–357 distribution of smile types during, 344 Duplay smiles, 342–343 dynamics of, 350 early development studies, 335–337 emergence of, 334–335 eye constriction-Duchenne smiles, 337–339 future research issues, 357 gaze aversion theories, 352 gazing at caregiver and, 351–352 infants’ perceptions of, 350–351 interactive development, 347–351 mouth opening-play smiles, 339–342 neonatal smiling, 333–334 neurophysiological mechanisms, 330–331 pragmatic aspects of, 354–357 quantity and quality analysis, 337–347

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Page 403

Subject Index rating studies, 344–345 referential communication and, 353–354 representativeness of, 354–355 social smiling development, 348–350 temperament-based studies, blind and sighted infants, 332–333 theoretical orientation, 328–330 social rank model, child’s development of demobilizing insecurity and, 127–128 “soft modularity,” evolutionary psychology and, 7–10, 23–24 source amnesia characteristics of, 41 frontal lobe function and, 50 source memory, childhood amnesia and development of, 54, 63–66 source monitoring framework autobiographical memory and, 46–47 episodic memory development and, 70–71 Spanish impairment disorders in, 144–145 processing limitations in SLI and, 160 spatial analysis, classroom environments, 285–287 spatial tasks, infantile amnesia and, 61–62 specific language impairment (SLI) basic principles of, 129–140 broader language deficit and, 148–151 cross-language comparisons, 141–146 current linguistic theory and, 146–147 degree of use comparisons in, 160–164 future research issues, 165–166 in German, Dutch, and Swedish, 143–144 grammatical morpheme difficulties and, 152–156 in Italian and Spanish, 144–145 processing limitations in, 156–164 spelling morphological awareness and, 317–318 morphological knowledge and, 309–313 information processing, 310–311 phonological transparency, 311–312 strategies for, 312–313 spelling skills, research on, 297–298 stability of classroom experience, outcomes assessment linked to, 266–267 “steeling” effects, children’s reactivity to family conflict and, 111 stereotyping academic and career-based gender identity and, 188–190

403

exclusion and, 176 family structure and inclusion patterns and, 190–191 friendship segregation and, 195–198 gender-based exclusion patterns and, 182–185 peer interactions and patterns in, 185–188 schools/communities as tools for, 199–200 stimulus mechanisms sensitization to interparental conflict and, 111–113 working memory and, 221–225 stress autonomy model, children’s reactivity to family conflict and, 111 “suitcase” metaphor for working memory research, task-switching process and, 228–229 supervisory attentional system, working memory mechanisms and, 222–225 supportive family systems, security characteristics in, 117–118 Swedish processing limitations in SLI and, 158–160 specific language impairment in, 143–144 syntactic frames degree of use comparisons in speech language impairement and, 163–164 morphological knowledge and, 302–303

T task completion, working memory mechanisms and, 220–221 task-switching hypothesis complex span task models and, 237–239 endurance of working memory and variables in, 230–232 integration with other working memory research, 242–244 representational overlap and forgetting research and, 235–237 time-based resource-sharing model of working memory and, 233–235 working memory in children and, 228–239 teacher characteristics academic achievement and role of, 277–280 classroom experiences linked to, 267–270 class size effects on, 269 educational policies’ impact on, 270–275 experience and education levels and effectiveness of, 270–273

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Subject Index

outcomes assessment in educational research and, 258–260 qualitative analysis of, 287–288 temporal dynamics endurance of working memory and, 230–232 integrated working memory theories and, 243–244 recall chronometry in working memory and, 233 in working memory research, 227–228 temporary information loss, task-switching process and, 228–229 temperament-based studies, smiling in blind and sighted infants, 332–333 theory-of-mind mechanism, evolutionary psychology and, 8–10 time-based resource-sharing model, working memory research and, 233–235 timing, developmental systems theory and, 12–14 toy preferences future research on, 205–209 gender-based exclusion patterns and, 183–185 peer-based inclusion and, 191–192 transactional response mechanisms, children’s reactivity to family conflict and, 115–116

U unitary memory store, hypothesis of, 44 universal grammar, evolved probabilistic cognitive mechanisms and, 24 utterance-final processing bias, specific language impairment and, 158

V verbal information complex span tasks in working memory research and, 237–239 working memory and, 223–225 verbs, processing of, specific linguistic impairment and deficits in, 148–151 victimization, exclusion and, 176 visual-paired-comparison (VPC) task early childhood memory and, 52–54 infantile amnesia and, 58 visual-search paradigm, prepared learning and, 27 visuospatial information complex span tasks in working memory research and, 237–239 working memory and, 223–225

visuospatial sketchpad (VSSP) system children’s development of working memory and, 225–227 working memory mechanisms and, 221–225 vocabulary skills memory span development and, 225–227 morphological awareness and, 315–319 specific language impairment and, 140, 148–151

W whole-group instructional techniques, grade-level analysis of, 265–266 word acquisition memory span development and, 225–227 morphological analysis and, 300–302 reading skills and, 304–309 morphological knowledge and, 298–300 word-order errors, German, Dutch and Swedish language impairment and, 143–144 word-specific paradigms, degree of use comparisons in SLI and, 161–164 working memory model architecture of, 223–225 in children, 219–221 complex span construction, 237–239 continuous and qualitaative changes in, 241 counting span in children and, 227–239 development in children of, 225–227 endurance of, 230–233 future research issues, 245–246 general framework, 223–225 history of research on, 221–225 integrated theories of, 241–244 language deficits and, 149–151 processing limitations and, 156–158 recall chronometry, 233 representational overlap and forgetting mechanisms, 235–237 research issues, 239–241 specific language impairment and, 147–164 task-switching model, 227–232 temporal dynamics, 229–230 time-based resource-sharing model, 233–235 writing deficits morphological knowledge and, 307–308 morphological spelling strategies and, 312–313

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Contents of Previous Volumes Volume 1

A Developmental Approach to Learning and Cognition Eugene S. Gollin Evidence for a Hierarchical Arrangement of Learning Processes Sheldon H. White Selected Anatomic Variables Analyzed for Interage Relationships of the Size-Size, Size-Gain, and Gain-Gain Varieties Howard V. Meredith

Responses of Infants and Children to Complex and Novel Stimulation Gordon N. Cantor Word Associations and Children’s Verbal Behavior David S. Palermo Change in the Stature and Body Weight of North American Boys during the Last 80 Years Howard V. Meredith Discrimination Learning Set in Children Hayne W. Reese Learning in the First Year of Life Lewis P. Lipsitt Some Methodological Contributions from a Functional Analysis of Child Development Sidney W. Bijou and Donald M. Baer The Hypothesis of Stimulus Interaction and an Explanation of Stimulus Compounding Charles C. Spiker The Development of ‘‘Overconstancy’’ in Space Perception Joachim F. Wohlwill Miniature Experiments in the Discrimination Learning of Retardates Betty J. House and David Zeaman

AUTHOR INDEX—SUBJECT INDEX

Volume 3 Infant Sucking Behavior and Its Modification Herbert Kaye The Study of Brain Electrical Activity in Infants Robert J. Ellingson Selective Auditory Attention in Children Eleanor E. Maccoby Stimulus Definition and Choice Michael D. Zeiler Experimental Analysis of Inferential Behavior in Children Tracy S. Kendler and Howard H. Kendler Perceptual Integration in Children Herbert L. Pick, Jr., Anne D. Pick, and Robert E. Klein Component Process Latencies in Reaction Times of Children and Adults Raymond H. Hohle

AUTHOR INDEX—SUBJECT INDEX

Volume 2 The Paired-Associates Method in the Study of Conflict Alfred Castaneda Transfer of Stimulus Pretraining to Motor Paired-Associate and Discrimination Learning Tasks Joan H. Cantor The Role of the Distance Receptors in the Development of Social Responsiveness Richard H. Walters and Ross D. Parke Social Reinforcement of Children’s Behavior Harold W. Stevenson Delayed Reinforcement Effects Glenn Terrell

AUTHOR INDEX—SUBJECT INDEX

Volume 4 Developmental Studies of Figurative Perception David Elkind The Relations of Short-Term Memory to Development and Intelligence John M. Belmont and Earl C. Butterfield

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Contents of Previous Volumes

Learning, Developmental Research, and Individual Differences Frances Degen Horowitz Psychophysiological Studies in Newborn Infants S. J. Hutt, H. G. Lenard, and H. F. R. Prechtl Development of the Sensory Analyzers during Infancy Yvonne Brackbill and Hiram E. Fitzgerald The Problem of Imitation Justin Aronfreed AUTHOR INDEX—SUBJECT INDEX

Volume 5 The Development of Human Fetal Activity and Its Relation to Postnatal Behavior Tryphena Humphrey Arousal Systems and Infant Heart Rate Responses Frances K. Graham and Jan C. Jackson Specific and Diversive Exploration Corinne Hutt Developmental Studies of Mediated Memory John H. Flavell Development and Choice Behavior in Probabilistic and Problem-Solving Tasks L. R. Goulet and Kathryn S. Goodwin AUTHOR INDEX—SUBJECT INDEX

Volume 6 Incentives and Learning in Children Sam L. Witryol Habituation in the Human Infant Wendell E. Jeffrey and Leslie B. Cohen Application of Hull-Spence Theory to the Discrimination Learning of Children Charles C. Spiker Growth in Body Size: A Compendium of Findings on Contemporary Children Living in Different Parts of the World Howard V. Meredith Imitation and Language Development James A. Sherman

Conditional Responding as a Paradigm for Observational, Imitative Learning and Vicarious-Reinforcement Jacob L. Gewirtz AUTHOR INDEX—SUBJECT INDEX

Volume 7 Superstitious Behavior in Children: An Experimental Analysis Michael D. Zeiler Learning Strategies in Children from Different Socioeconomic Levels Jean L. Bresnahan and Martin M. Shapiro Time and Change in the Development of the Individual and Society Klaus F. Riegel The Nature and Development of Early Number Concepts Rochel Gelman Learning and Adaptation in Infancy: A Comparison of Models Arnold J. Sameroff AUTHOR INDEX—SUBJECT INDEX

Volume 8 Elaboration and Learning in Childhood and Adolescence William D. Rohwer, Jr. Exploratory Behavior and Human Development Jum C. Nunnally and L. Charles Lemond Operant Conditioning of Infant Behavior: A Review Robert C. Hulsebus Birth Order and Parental Experience in Monkeys and Man G. Mitchell and L. Schroers Fear of the Stranger: A Critical Examination Harriet L. Rheingold and Carol O. Eckerman Applications of Hull–Spence Theory to the Transfer of Discrimination Learning in Children Charles C. Spiker and Joan H. Cantor AUTHOR INDEX—SUBJECT INDEX

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Contents of Previous Volumes Volume 9 Children’s Discrimination Learning Based on Identity or Difference Betty J. House, Ann L. Brown, and Marcia S. Scott Two Aspects of Experience in Ontogeny: Development and Learning Hans G. Furth The Effects of Contextual Changes and Degree of Component Mastery on Transfer of Training Joseph C. Campione and Ann L. Brown Psychophysiological Functioning, Arousal, Attention, and Learning during the First Year of Life Richard Hirschman and Edward S. Katkin Self-Reinforcement Processes in Children John C. Masters and Janice R. Mokros AUTHOR INDEX—SUBJECT INDEX

Volume 10 Current Trends in Developmental Psychology Boyd R. McCandless and Mary Fulcher Geis The Development of Spatial Representations of Large-Scale Environments Alexander W. Siegel and Sheldon H. White Cognitive Perspectives on the Development of Memory John W. Hagen, Robert H. Jongeward, Jr., and Robert V. Kail, Jr. The Development of Memory: Knowing, Knowing About Knowing, and Knowing How to Know Ann L. Brown Developmental Trends in Visual Scanning Mary Carol Day The Development of Selective Attention: From Perceptual Exploration to Logical Search John C. Wright and Alice G. Vlietstra AUTHOR INDEX—SUBJECT INDEX

Volume 11 The Hyperactive Child: Characteristics, Treatment, and Evaluation of Research Design Gladys B. Baxley and Judith M. LeBlanc

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Peripheral and Neurochemical Parallels of Psychopathology: A Psychophysiological Model Relating Autonomic Imbalance to Hyperactivity, Psychopathy, and Autism Stephen W. Porges Constructing Cognitive Operations Linguistically Harry Beilin Operant Acquisition of Social Behaviors in Infancy: Basic Problems and Constraints W. Stuart Millar Mother-Infant Interaction and Its Study Jacob L. Gewirtz and Elizabeth F. Boyd Symposium on Implications of Life-Span Developmental Psychology for Child Development: Introductory Remarks Paul B. Baltes Theory and Method in Life-Span Developmental Psychology: Implications for Child Development Aletha Huston-Stein and Paul B. Baltes The Development of Memory: Life-Span Perspectives Hayne W. Reese Cognitive Changes during the Adult Years: Implications for Developmental Theory and Research Nancy W. Denney and John C. Wright Social Cognition and Life-Span Approaches to the Study of Child Development Michael J. Chandler Life-Span Development of the Theory of Oneself: Implications for Child Development Orville G. Brim, Jr. Implication of Life-Span Developmental Psychology for Childhood Education Leo Montada and Sigrun-Heide Filipp AUTHOR INDEX—SUBJECT INDEX

Volume 12 Research between 1960 and 1970 on the Standing Height of Young Children in Different Parts of the World Howard V. Meredith The Representation of Children’s Knowledge David Klahr and Robert S. Siegler

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Contents of Previous Volumes

Chromatic Vision in Infancy Marc H. Bornstein Developmental Memory Theories: Baldwin and Piaget Bruce M. Ross and Stephen M. Kerst Child Discipline and the Pursuit of Self: An Historical Interpretation Howard Gadlin Development of Time Concepts in Children William J. Friedman AUTHOR INDEX—SUBJECT INDEX

Volume 13

Sibship-Constellation Effects on Psychosocial Development, Creativity, and Health Mazie Earle Wagner, Herman J. P. Schubert,and Daniel S. P. Schubert The Development of Understanding of the Spatial Terms Front and Back Lauren Julius Harris and Ellen A. Strommen The Organization and Control of Infant Sucking C. K. Crook Neurological Plasticity, Recovery from Brain Insult, and Child Development Ian St. James-Roberts

Coding of Spatial and Temporal Information in Episodic Memory Daniel B. Berch A Developmental Model of Human Learning Barry Gholson and Harry Beilin The Development of Discrimination Learning: A Levels-of-Functioning Explanation Tracy S. Kendler The Kendler Levels-of-Functioning Theory: Comments and an Alternative Schema Charles C. Spiker and Joan H. Cantor Commentary on Kendler’s Paper: An Alternative Perspective Barry Gholson and Therese Schuepfer Reply to Commentaries Tracy S. Kendler On the Development of Speech Perception: Mechanisms and Analogies Peter D. Eimas and Vivien C. Tartter The Economics of Infancy: A Review of Conjugate Reinforcement Carolyn Kent Rovee-Collier and Marcy J. Gekoski Human Facial Expressions in Response to Taste and Smell Stimulation Jacob E. Steiner

AUTHOR INDEX—SUBJECT INDEX

AUTHOR INDEX—SUBJECT INDEX

The History of the Boyd R. McCandless Young Scientist Awards: The First Recipients David S. Palermo Social Bases of Language Development: A Reassessment Elizabeth Bates, Inge Bretherton, Marjorie Beeghly-Smith, and Sandra McNew

Volume 14 Development of Visual Memory in Infants John S. Werner and Marion Perlmutter

Volume 15 Visual Development in Ontogenesis: Some Reevaluations Jüri Allik and Jaan Valsiner Binocular Vision in Infants: A Review and a Theoretical Framework Richard N. Aslin and Susan T. Dumais Validating Theories of Intelligence Earl C. Butterfield, Dennis Siladi, and John M. Belmont Cognitive Differentiation and Developmental Learning William Fowler Children’s Clinical Syndromes and Generalized Expectations of Control Fred Rothbaum AUTHOR INDEX—SUBJECT INDEX

Volume 16

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Contents of Previous Volumes Perceptual Anisotropies in Infancy: Ontogenetic Origins and Implications of Inequalities in Spatial Vision Marc H. Bornstein Concept Development Martha J. Farah and Stephen M. Kosslyn Production and Perception of Facial Expressions in Infancy and Early Childhood Tiffany M. Field and Tedra A. Walden Individual Differences in Infant Sociability: Their Origins and Implications for Cognitive Development Michael E. Lamb The Development of Numerical Understandings Robert S. Siegler and Mitchell Robinson AUTHOR INDEX—SUBJECT INDEX

Volume 17 The Development of Problem-Solving Strategies Deanna Kuhn and Erin Phelps Information Processing and Cognitive Development Robert Kail and Jeffrey Bisanz Research between 1950 and 1980 on Urban–Rural Differences in Body Size and Growth Rate of Children and Youths Howard V. Meredith Word Meaning Acquisition in Young Children: A Review of Theory and Research Pamela Blewitt Language Play and Language Acquisition Stan A. Kuczaj II The Child Study Movement: Early Growth and Development of the Symbolized Child Alexander W. Siegel and Sheldon H. White AUTHOR INDEX—SUBJECT INDEX

Volume 18 The Development of Verbal Communicative Skills in Children Constance R. Schmidt and Scott G. Paris

409

Auditory Feedback and Speech Development Gerald M. Siegel, Herbert L. Pick, Jr., and Sharon R. Garber Body Size of Infants and Children around the World in Relation to Socioeconomic Status Howard V. Meredith Human Sexual Dimorphism: Its Cost and Benefit James L. Mosley and Eileen A. Stan Symposium on Research Programs: Rational Alternatives to Kuhn’s Analysis of Scientific Progress—Introductory Remarks Hayne W. Reese, Chairman World Views and Their Influence on Psychological Theory and Research: Kuhn-Lakatos-Laudan Willis F. Overton The History of the Psychology of Learning as a Rational Process: Lakatos versus Kuhn Peter Barker and Barry Gholson Functionalist and Structuralist Research Programs in Developmental Psychology: Incommensurability or Synthesis? Harry Beilin In Defense of Kuhn: A Discussion of His Detractors David S. Palermo Comments on Beilin’s Epistemology and Palermo’s Defense of Kuhn Willis F. Overton From Kuhn to Lakatos to Laudan Peter Barker and Barry Gholson Overton’s and Palermo’s Relativism: One Step Forward, Two Steps Back Harry Beilin AUTHOR INDEX—SUBJECT INDEX

Volume 19 Response to Novelty: Continuity versus Discontinuity in the Developmental Course of Intelligence Cynthia A. Berg and Robert J. Sternberg Metaphoric Competence in Cognitive and Language Development Marc Marschark and Lynn Nall

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Contents of Previous Volumes

The Concept of Dimensions in Developmental Research Stuart I. Offenbach and Francine C. Blumberg Effects of the Knowledge Base on Children’s Memory Strategies Peter A. Ornstein and Mary J. Naus Effects of Sibling Spacing on Intelligence, Interfamilial Relations, Psychosocial Characteristics, and Mental and Physical Health Mazie Earle Wagner, Herman J. P. Schubert, and Daniel S. P. Schubet Infant Visual Preferences: A Review and New Theoretical Treatment Martin S. Banks and Arthur P. Ginsburg AUTHOR INDEX—SUBJECT INDEX

Volume 20 Variation in Body Stockiness among and within Ethnic Groups at Ages from Birth to Adulthood Howard V. Meredith The Development of Conditional Reasoning: An Iffy Proposition David P. O’Brien Content Knowledge: Its Role, Representation, and Restructuring in Memory Development Michelene T. H. Chi and Stephen J. Ceci Descriptions: A Model of Nonstrategic Memory Development Brian P. Ackerman Reactivation of Infant Memory: Implications for Cognitive Development Carolyn Rovee-Collier and Harlene Hayne Gender Segregation in Childhood Eleanor E. Maccoby and Carol Nagy Jacklin Piaget, Attentional Capacity, and the Functional Implications of Formal Structure Michael Chapman INDEX

Volume 21 Social Development in Infancy: A 25-Year Perspective Ross D. Parke

On the Uses of the Concept of Normality in Developmental Biology and Psychology Eugene S. Gollin, Gary Stahl, and Elyse Morgan Cognitive Psychology: Mentalistic or Behavioristic? Charles C. Spiker Some Current Issues in Children’s Selective Attention Betty J. House Children’s Learning Revisited: The Contemporary Scope of the Modified Spence Discrimination Theory Joan H. Cantor and Charles C. Spiker Discrimination Learning Set in Children Hayne W. Reese A Developmental Analysis of Rule-Following Henry C. Riegler and Donald M. Baer Psychological Linguistics: Implications for a Theory of Initial Development and a Method for Research Sidney W. Bijou Psychic Conflict and Moral Development Gordon N. Cantor and David A. Parton Knowledge and the Child’s Developing Theory of the World David S. Palermo Childhood Events Recalled by Children and Adults David B. Pillemer and Sheldon H. White INDEX

Volume 22 The Development of Representation in Young Children Judy S. DeLoache Children’s Understanding of Mental Phenomena David Estes, Henry M. Wellman, and Jacqueline D. Woolley Social Influences on Children’s Cognition: State of the Art and Future Directions Margarita Azmitia and Marion Perlmutter Understanding Maps as Symbols: The Development of Map Concepts Lynn S. Liben and Roger M. Downs The Development of Spatial Perspective Taking Nora Newcombe

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Contents of Previous Volumes Developmental Studies of Alertness and Encoding Effects of Stimulus Repetition Daniel W. Smothergill and Alan G. Kraut Imitation in Infancy: A Critical Review Claire L. Poulson, Leila Regina de Paula Nunes, and Steven F. Warren AUTHOR INDEX—SUBJECT INDEX

Volume 23 The Structure of Developmental Theory Willis F. Overton Questions a Satisfying Developmental Theory Would Answer: The Scope of a Complete Explanation of Development Phenomena Frank B. Murray The Development of World Views: Toward Future Synthesis? Ellin Kofsky Scholnick Metaphor, Recursive Systems, and Paradox in Science and Developmental Theory Willis F. Overton Children’s Iconic Realism: Object versus Property Realism Harry Beilin and Elise G. Pearlman The Role of Cognition in Understanding Gender Effects Carol Lynn Martin Development of Processing Speed in Childhood and Adolescence Robert Kail Contextualism and Developmental Psychology Hayne W. Reese Horizontality of Water Level: A Neo-Piagetian Developmental Review Juan Pascual-Leone and Sergio Morra AUTHOR INDEX—SUBJECT INDEX

Volume 24 Music and Speech Processing in the First Year of Life Sandra E. Trehub, Laurel J. Trainor, and Anna M. Unyk

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Effects of Feeding Method on Infant Temperament John Worobey The Development of Reading Linda S. Siegel Learning to Read: A Theoretical Synthesis John P. Rack, Charles Hulme, and Margaret J. Snowling Does Reading Make You Smarter? Literacy and the Development of Verbal Intelligence Keith E. Stanovich Sex-of-Sibling Effects: Part I. Gender Role, Intelligence, Achievement, and Creativity Mazie Earle Wagner, Herman J. P. Schubert, and Daniel S. P. Schubert The Concept of Same Linda B. Smith Planning as Developmental Process Jacquelyn Baker-Sennett, Eugene Matusov, and Barbara Rogoff AUTHOR INDEX—SUBJECT INDEX

Volume 25 In Memoriam: Charles C. Spiker (1925–1993) Lewis P. Lipsitt Developmental Differences in Associative Memory: Strategy Use, Mental Effort, and Knowledge Access Interactions Daniel W. Kee A Unifying Framework for the Development of Children’s Activity Memory Hilary Horn Ratner and Mary Ann Foley Strategy Utilization Deficiencies in Children: When, Where, and Why Patricia H. Miller and Wendy L. Seier The Development of Children’s Ability to Use Spatial Representations Mark Blades and Christopher Spencer Fostering Metacognitive Development Linda Baker The HOME Inventory: Review and Reflections Robert H. Bradley Social Reasoning and the Varieties of Social Experiences in Cultural Contexts Elliot Turiel and Cecilia Wainryb

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Contents of Previous Volumes

Mechanisms in the Explanation of Developmental Change Harry Beilin

The Foundation of Piaget’s Theories: Mental and Physical Action Harry Beilin and Gary Fireman

AUTHOR INDEX—SUBJECT INDEX

AUTHOR INDEX—SUBJECT INDEX

Volume 26

Volume 28

Preparing to Read: The Foundations of Literacy Ellen Bialystok The Role of Schemata in Children’s Memory Denise Davidson The Interaction of Knowledge, Aptitude, and Strategies in Children’s Memory Performance David F. Bjorklund and Wolfgang Schneider Analogical Reasoning and Cognitive Development Usha Goswami Sex-of-Sibling Effects: A Review Part II. Personality and Mental and Physical Health Mazie Earle Wagner, Herman J. P. Schubert, and Daniel S. P. Schubert Input and Learning Processes in First Language Acquisition Ernst L. Moerk

Variability in Children’s Reasoning Karl S. Rosengren and Gregory S. Braswell Fuzzy-Trace Theory: Dual Processes in Memory, Reasoning, and Cognitive Neuroscience C. J. Brainerd and V. F. Reyna Relational Frame Theory: A Post-Skinnerian Account of Human Language and Cognition Yvonne Barnes-Holmes, Steven C. Hayes, Dermot Barnes-Holmes, and Bryan Roche The Continuity of Depression across the Adolescent Transition Shelli Avenevoli and Laurence Steinberg The Time of Our Lives: Self-Continuity in Native and Non-Native Youth Michael J. Chandler AUTHOR INDEX—SUBJECT INDEX

AUTHOR INDEX—SUBJECT INDEX Volume 29 Volume 27 From Form to Meaning: A Role for Structural Alignment in the Acquisition of Language Cynthia Fisher The Role of Essentialism in Children’s Concepts Susan A. Gelman Infants’ Use of Prior Experiences with Objects in Object Segregation: Implications for Object Recognition in Infancy Amy Needham and Avani Modi Perseveration and Problem Solving in Infancy Andréa Aguiar and Renée Baillargeon Temperament and Attachment: One Construct or Two? Sarah C. Mangelsdorf and Cynthia A. Frosch

The Search for What is Fundamental in the Development of Working Memory Nelson Cowan, J. Scott Saults, and Emily M. Elliott Culture, Autonomy, and Personal Jurisdiction in Adolescent–Parent Relationships Judith G. Smetana Maternal Responsiveness and Early Language Acquisition Catherine S. Tamis-Lemonda and Marc H. Bornstein Schooling as Cultural Process: Working Together and Guidance by Children from Schools Differing in Collaborative Practices Eugene Matusov, Nancy Bell, and Barbara Rogoff

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Contents of Previous Volumes Beyond Prototypes: Asymmetries in Infant Categorization and What They Teach Us about the Mechanisms Guiding Early Knowledge Acquisition Paul C. Quinn Peer Relations in the Transition to Adolescence Carollee Howes and Julie Wargo Aikins AUTHOR INDEX—SUBJECT INDEX

Volume 30 Learning to Keep Balance Karen Adolph Sexual Selection and Human Life History David C. Geary Developments in Early Recall Memory: Normative Trends and Individual Differences Patricia J. Bauer, Melissa M. Burch, and Erica E. Kleinknecht Intersensory Redundancy Guides Early Perceptual and Cognitive Development Lorraine E. Bahrick and Robert Lickliter Children’s Emotion-Related Regulation Nancy Eisenberg and Amanda Sheffield Morris Maternal Sensitivity and Attachment in Atypical Groups L. Beckwith, A. Rozga, and M. Sigman Influences of Friends and Friendships: Myths, Truths, and Research Recommendations Thomas J. Berndt and Lonna M. Murphy AUTHOR INDEX—SUBJECT INDEX

Volume 31 Beyond Point And Shoot: Children’s Developing Understanding of Photographs as Spatial and Expressive Representations Lynn S. Liben Probing the Adaptive Significance of Children’s Behavior and Relationships in the School Context: A Child by Environment Perspective Gary W. Ladd

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The Role of Letter Names in the Acquisition of Literacy Rebecca Treiman and Brett Kessler Early Understandings of Emotion, Morality, and Self: Developing a Working Model Ross A. Thompson, Deborah J. Laible and Lenna L. Ontai Working Memory in Infancy Kevin A. Pelphrey and J. Steven Reznick The Development of a Differentiated Sense of the Past and the Future William J. Friedman The Development of Cognitive Flexibility and Language Abilities Gedeon O. Deák A Bio-Social-Cognitive Approach to Understanding and Promoting the Outcomes of Children with Medical and Physical Disorders Daphne Blunt Bugental and David A. Beaulieu Expanding Our View of Context: The Bio-ecological Environment and Development Theodore D. Wachs Pathways to Early Literacy: The Complex Interplay of Child, Family, and Sociocultural Factors Megan M. McClelland, Maureen Kessenich, and Frederick J. Morrison AUTHOR INDEX—SUBJECT INDEX

Volume 32 From the Innocent to the Intelligent Eye: The Early Development of Pictorial Competence Georgene L. Troseth, Sophia L. Pierroutsakos, and Judy S. DeLoache Bringing Culture into Relief: Cultural Contributions to the Development of Children’s Planning Skills Mary Gauvain A Dual-Process Model of Adolescent Development: Implications for Decision Making, Reasoning, and Identity Paul A. Klaczynski

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Contents of Previous Volumes

The High Price of Affluence Suniya S. Luthar and Chris C. Sexton Attentional Inertia in Children’s Extended Looking at Television John E. Richards and Daniel R. Anderson Understanding Classroom Competence: The Role of Social-Motivational and SelfProcesses Kathryn R. Wentzel Continuities and Discontinuities in Infants’ Representation of Objects and Events Rachel E. Keen and Neil E. Berthier The Mechanisms of Early Categorization and Induction: Smart or Dumb Infants? David H. Rakison and Erin R. Hahn AUTHOR INDEX—SUBJECT INDEX

Volume 33 A Computational Model of Conscious and Unconscious Strategy Discovery Robert Siegler and Roberto Araya Out-of-School Settings as a Developmental Context for Children and Youth Deborah Lowe Vandell, Kim M. Pierce and Kimberly Dadisman Mechanisms of Change in the Development of Mathematical Reasoning Martha W. Alibali A Social Identity Approach to Ethnic Differences in Family Relationships during Adolescence Andrew J. Fuligni and Lisa Flook What Develops in Language Development? LouAnn Gerken The Role of Children’s Competence Experiences in the Socialization Process: A Dynamic Process Framework for the Academic Arena Eva M. Pomerantz, Qian Wang and Florrie Ng The Infant Origins of Intentional Understanding Amanda L. Woodward

Analyzing Comorbidity Bruce F. Pennington, Erik Willcutt and Soo Hyun Rhee Number Words and Number Concepts: The Interplay of Verbal and Nonverbal Quantification in Early Childhood Kelly S. Mix, Catherine M. Sandhofer and Arthur J. Baroody AUTHOR INDEX—SUBJECT INDEX

Volume 34 Mapping Sound to Meaning: Connections Between Learning About Sounds and Learning About Words Jenny R. Saffran and Katharine Graf Estes A Developmental Intergroup Theory of Social Stereotypes and Prejudice Rebecca S. Bigler and Lynn S. Liben Income Poverty, Poverty Co-Factors, and the Adjustment of Children in Elementary School Brian P. Ackerman and Eleanor D. Brown I Thought She Knew That Would Hurt My Feelings: Developing Psychological Knowledge and Moral Thinking Cecilia Wainryb and Beverely A. Brehl Home Range and The Development of Children’s Way Finding Edward H. Cornel and C. Donald Heth The Development and Neural Bases of Facial Emotion Recognition Jukka M. Leppänen and Charles A. Nelson Children’s Suggestibility: Charecterestics and Mechanisms Stephen J. Ceci and Maggie Bruck The Emergence and Basis of Endogenous Attention in Infancy and Early Childhood John Colombo and Carol L. Cheatham The Probabilistic Epigenesis of Knowledge James A. Dixon and Elizabeth Kelley AUTHOR INDEX—SUBJECT INDEX